wav2vec2-large-lv60_phoneme-timit_english_timit-4k_simplified
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%)
Model description
Trained on a simplified version of the TIMIT phone set.
Intended uses & limitations
Merged Phonemes
- 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
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| 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 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.2