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wav2vec2-large-xls-r-300m-sr-v4
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SR dataset. It achieves the following results on the evaluation set:
- Loss: 0.5570
- Wer: 0.3038
Evaluation Commands
- To evaluate on mozilla-foundation/common_voice_8_0 with test split
python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-sr-v4 --dataset mozilla-foundation/common_voice_8_0 --config sr --split test --log_outputs
- To evaluate on speech-recognition-community-v2/dev_data
python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-sr-v4 --dataset speech-recognition-community-v2/dev_data --config sr --split validation --chunk_length_s 10 --stride_length_s 1
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 800
- num_epochs: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 8.2934 | 7.5 | 300 | 2.9777 | 0.9995 |
| 1.5049 | 15.0 | 600 | 0.5036 | 0.4806 |
| 0.3263 | 22.5 | 900 | 0.5822 | 0.4055 |
| 0.2008 | 30.0 | 1200 | 0.5609 | 0.4032 |
| 0.1543 | 37.5 | 1500 | 0.5203 | 0.3710 |
| 0.1158 | 45.0 | 1800 | 0.6458 | 0.3985 |
| 0.0997 | 52.5 | 2100 | 0.6227 | 0.4013 |
| 0.0834 | 60.0 | 2400 | 0.6048 | 0.3836 |
| 0.0665 | 67.5 | 2700 | 0.6197 | 0.3686 |
| 0.0602 | 75.0 | 3000 | 0.5418 | 0.3453 |
| 0.0524 | 82.5 | 3300 | 0.5310 | 0.3486 |
| 0.0445 | 90.0 | 3600 | 0.5599 | 0.3374 |
| 0.0406 | 97.5 | 3900 | 0.5958 | 0.3327 |
| 0.0358 | 105.0 | 4200 | 0.6017 | 0.3262 |
| 0.0302 | 112.5 | 4500 | 0.5613 | 0.3248 |
| 0.0285 | 120.0 | 4800 | 0.5659 | 0.3462 |
| 0.0213 | 127.5 | 5100 | 0.5568 | 0.3206 |
| 0.0215 | 135.0 | 5400 | 0.6524 | 0.3472 |
| 0.0162 | 142.5 | 5700 | 0.6223 | 0.3458 |
| 0.0137 | 150.0 | 6000 | 0.6625 | 0.3313 |
| 0.0114 | 157.5 | 6300 | 0.5739 | 0.3336 |
| 0.0101 | 165.0 | 6600 | 0.5906 | 0.3285 |
| 0.008 | 172.5 | 6900 | 0.5982 | 0.3112 |
| 0.0076 | 180.0 | 7200 | 0.5399 | 0.3094 |
| 0.0071 | 187.5 | 7500 | 0.5387 | 0.2991 |
| 0.0057 | 195.0 | 7800 | 0.5570 | 0.3038 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.2
- Tokenizers 0.11.0
