wav2vec-commonvoice-2
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2220
- Wer: 0.1269
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6557 | 1.0 | 1453 | 0.2339 | 0.1604 |
| 0.1267 | 2.0 | 2906 | 0.2057 | 0.1422 |
| 0.1008 | 3.0 | 4359 | 0.1963 | 0.1356 |
| 0.0846 | 4.0 | 5812 | 0.2037 | 0.1308 |
| 0.0727 | 5.0 | 7265 | 0.2029 | 0.1299 |
| 0.0639 | 6.0 | 8718 | 0.2064 | 0.1301 |
| 0.0559 | 7.0 | 10171 | 0.2061 | 0.1273 |
| 0.0493 | 8.0 | 11624 | 0.2108 | 0.1278 |
| 0.0437 | 9.0 | 13077 | 0.2183 | 0.1273 |
| 0.0398 | 10.0 | 14530 | 0.2220 | 0.1269 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for aman-batazia/wav2vec-commonvoice-2
Base model
facebook/w2v-bert-2.0Evaluation results
- Wer on common_voice_17_0validation set self-reported0.127