sparkly-3.2-train
2
24.0B
BF16
license:apache-2.0
by
ToastyPigeon
Code Model
OTHER
24B params
New
2 downloads
Early-stage
Edge AI:
Mobile
Laptop
Server
54GB+ RAM
Mobile
Laptop
Server
Quick Summary
workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts This model is a fine-tuned version of Gryphe/Codex-24B-Small-3.
Device Compatibility
Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
23GB+ RAM
Code Examples
=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69=== Model Configuration ===yaml
# === Model Configuration ===
base_model: Gryphe/Codex-24B-Small-3.2
load_in_8bit: false
load_in_4bit: true
# === HF Configuration ===
#hub_model_id: ToastyPigeon/sparkly-3.2-train
#hub_strategy: "checkpoint"
# === Training Setup ===
num_epochs: 1
micro_batch_size: 1
gradient_accumulation_steps: 8
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
max_steps: 10
# === Evaluation ===
#val_set_size: 0.01
#evals_per_epoch: 5
#eval_steps: 20
#max_steps: 60
#eval_table_size:
#eval_max_new_tokens: 128
#eval_sample_packing: true
eval_strategy: "no"
# === LoRA Configuration ===
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 16
lora_dropout: 0.5
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
#peft_use_rslora: true
lora_modules_to_save:
- embed_tokens
# - lm_head
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
# === Hyperparameter Configuration ===
#optimizer: apollo_adamw_layerwise
warmup_steps: 0
#optimizer: adamw_torch_fused
optimizer: paged_adamw_8bit
#optim_args:
# enable_stochastic_rounding: true
# enable_cautious: true
# enable_8bit: true
# Apollo-mini configuration:
#optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100"
# Regular Apollo configuration:
# optim_args:
#optim_target_modules: all_linear
learning_rate: 1e-5
lr_scheduler: rex
#cosine_min_lr_ratio: 0.2
#lr_scheduler: cosine_with_min_lr
#lr_scheduler_kwargs:
# cosine_min_lr: 1e-6
weight_decay: 0.01
max_grad_norm: 1.0
#warmup_steps: 0
#warmup_ratio: 0.025
# === Data Configuration ===
#chat_template: jinja
#chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters)
chat_template: chatml
#special_tokens:
# eos_token: "</s>"
tokenizer_use_mistral_common: true
shuffle_merged_datasets: true
datasets:
- path: ToastyPigeon/cowriter-instruct
type: chat_template
data_files:
- cowriter-4k.json
- cowriter-8k.json
- path: allura-org/EU01-S2
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: allenai/tulu-3-sft-personas-instruction-following
type: chat_template
split: train[:10%]
- path: ToastyPigeon/mixed-medical-reasoning-formatted
type: chat_template
data_files: mixed-medical-thinking.json
split: train[:10%]
- path: ToastyPigeon/steve-and-marvin
type: completion
data_files: marvin.json
- path: ToastyPigeon/new-story-dataset
type: customcompletion-regex
data_files: new-story-dataset-v2.json
- path: allura-org/fujin-instruct-v2
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/some-rp-extended
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/gutenberg-sft
type: customchatml-regex
field_messages: conversations
message_property_mappings:
role: from
content: value
- path: ToastyPigeon/SpringDragon
type: customcompletion-regex
split: train
- path: ToastyPigeon/some-erotica
type: customcompletion-regex
split: train[:100]
dataset_prepared_path: last_run_prepared
# === Plugins ===
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# === Hardware Optimization ===
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
#liger_fused_linear_cross_entropy: true
cut_cross_entropy: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
# === FSDP Config ===
# === Wandb Tracking ===
wandb_project: Mistral-3.2
# wandb_entity: [WANDB_ENTITY]
# wandb_name: [WANDB_RUN_NAME]
# === Checkpointing ===
saves_per_epoch: 1
save_total_limit: 1
# === Advanced Settings ===
output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts
bf16: auto
flash_attention: true
train_on_inputs: false
group_by_length: false
save_safetensors: true
logging_steps: 1
gc_steps: 10
seed: 69Deploy This Model
Production-ready deployment in minutes
Together.ai
Instant API access to this model
Production-ready inference API. Start free, scale to millions.
Try Free APIReplicate
One-click model deployment
Run models in the cloud with simple API. No DevOps required.
Deploy NowDisclosure: We may earn a commission from these partners. This helps keep LLMYourWay free.