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wav2vec2-common_voice-it-demo
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the COMMON_VOICE - IT dataset. It achieves the following results on the evaluation set:
- Loss: 0.3484
- Wer: 0.2368
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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.37 | 400 | 0.9124 | 0.7336 |
| 3.904 | 0.74 | 800 | 0.4753 | 0.5022 |
| 0.4384 | 1.1 | 1200 | 0.3941 | 0.3731 |
| 0.2985 | 1.47 | 1600 | 0.4007 | 0.3830 |
| 0.2719 | 1.84 | 2000 | 0.3576 | 0.3597 |
| 0.2719 | 2.21 | 2400 | 0.3571 | 0.3286 |
| 0.2158 | 2.57 | 2800 | 0.3465 | 0.3198 |
| 0.2054 | 2.94 | 3200 | 0.3162 | 0.2982 |
| 0.1783 | 3.31 | 3600 | 0.3295 | 0.3089 |
| 0.1495 | 3.68 | 4000 | 0.3248 | 0.3034 |
| 0.1495 | 4.04 | 4400 | 0.3101 | 0.3028 |
| 0.1397 | 4.41 | 4800 | 0.3588 | 0.3006 |
| 0.123 | 4.78 | 5200 | 0.3451 | 0.3041 |
| 0.115 | 5.15 | 5600 | 0.3333 | 0.2921 |
| 0.0947 | 5.51 | 6000 | 0.3331 | 0.2858 |
| 0.0947 | 5.88 | 6400 | 0.3536 | 0.2950 |
| 0.0952 | 6.25 | 6800 | 0.3344 | 0.2786 |
| 0.0778 | 6.62 | 7200 | 0.3363 | 0.2699 |
| 0.0744 | 6.99 | 7600 | 0.3246 | 0.2655 |
| 0.0648 | 7.35 | 8000 | 0.3390 | 0.2627 |
| 0.0648 | 7.72 | 8400 | 0.3405 | 0.2630 |
| 0.0591 | 8.09 | 8800 | 0.3367 | 0.2534 |
| 0.0527 | 8.46 | 9200 | 0.3448 | 0.2509 |
| 0.0461 | 8.82 | 9600 | 0.3379 | 0.2425 |
| 0.0408 | 9.19 | 10000 | 0.3491 | 0.2409 |
| 0.0408 | 9.56 | 10400 | 0.3456 | 0.2377 |
| 0.0393 | 9.93 | 10800 | 0.3488 | 0.2370 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.11.0
