excalibur12

wav2vec2-large-lv60phoneme-timitenglishtimit-4ksimplified This model is a fine-tuned version of facebook/wav2vec2-large-lv60 on the TIMIT dataset. It achieves the following results on the evaluation set: - Loss: 0.2796 - Phone Error Rate: 0.0838 (8.38%) Trained on a simplified version of the TIMIT phone set. - Based on error analysis for each phoneme from the original TIMIT phoneme set. - See this repo for detailed analysis. - ax-h → ax - axr → er - ix → ih - ux → uw - zh → z - em → m - en → n - eng → ng - nx → n - hv → hh The following hyperparameters were used during training: - learningrate: 0.0001 - trainbatchsize: 16 - evalbatchsize: 1 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lrschedulertype: linear - lrschedulerwarmupsteps: 300 - trainingsteps: 3000 - mixedprecisiontraining: Native AMP | Training Loss | Epoch | Step | Validation Loss | Phone Error Rate | |:-------------:|:-----:|:----:|:---------------:|:------:| | 7.3185 | 1.04 | 300 | 3.6437 | 0.9617 | | 2.5644 | 2.08 | 600 | 0.7668 | 0.1559 | | 0.6782 | 3.11 | 900 | 0.3794 | 0.1231 | | 0.4542 | 4.15 | 1200 | 0.3278 | 0.1164 | | 0.3834 | 5.19 | 1500 | 0.3043 | 0.1151 | | 0.3407 | 6.23 | 1800 | 0.2872 | 0.1119 | | 0.3179 | 7.27 | 2100 | 0.2842 | 0.1110 | | 0.2988 | 8.3 | 2400 | 0.2834 | 0.1102 | | 0.2834 | 9.34 | 2700 | 0.2826 | 0.1100 | | 0.2814 | 10.38 | 3000 | 0.2796 | 0.1100 | - Transformers 4.38.1 - Pytorch 2.0.1 - Datasets 2.16.1 - Tokenizers 0.15.2