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wav2vec2-large-xls-r-300m-spanish-small
This model is a fine-tuned version of jhonparra18/wav2vec2-large-xls-r-300m-spanish-custom on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.3596
- Wer: 0.2105
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1971 | 0.79 | 400 | 0.2169 | 0.2077 |
| 0.2293 | 1.58 | 800 | 0.2507 | 0.2418 |
| 0.2065 | 2.37 | 1200 | 0.2703 | 0.2459 |
| 0.1842 | 3.16 | 1600 | 0.2716 | 0.2495 |
| 0.1634 | 3.95 | 2000 | 0.2695 | 0.2510 |
| 0.1443 | 4.74 | 2400 | 0.2754 | 0.2435 |
| 0.1345 | 5.53 | 2800 | 0.3119 | 0.2654 |
| 0.1267 | 6.32 | 3200 | 0.3154 | 0.2573 |
| 0.1237 | 7.11 | 3600 | 0.3251 | 0.2666 |
| 0.1118 | 7.91 | 4000 | 0.3139 | 0.2503 |
| 0.1051 | 8.7 | 4400 | 0.3286 | 0.2573 |
| 0.0964 | 9.49 | 4800 | 0.3348 | 0.2587 |
| 0.0946 | 10.28 | 5200 | 0.3357 | 0.2587 |
| 0.0897 | 11.07 | 5600 | 0.3408 | 0.2590 |
| 0.0812 | 11.86 | 6000 | 0.3380 | 0.2560 |
| 0.079 | 12.65 | 6400 | 0.3304 | 0.2415 |
| 0.0753 | 13.44 | 6800 | 0.3557 | 0.2540 |
| 0.0717 | 14.23 | 7200 | 0.3507 | 0.2519 |
| 0.0691 | 15.02 | 7600 | 0.3554 | 0.2587 |
| 0.0626 | 15.81 | 8000 | 0.3619 | 0.2520 |
| 0.0661 | 16.6 | 8400 | 0.3609 | 0.2564 |
| 0.0582 | 17.39 | 8800 | 0.3818 | 0.2520 |
| 0.0556 | 18.18 | 9200 | 0.3685 | 0.2410 |
| 0.0515 | 18.97 | 9600 | 0.3658 | 0.2367 |
| 0.0478 | 19.76 | 10000 | 0.3701 | 0.2413 |
| 0.0486 | 20.55 | 10400 | 0.3681 | 0.2371 |
| 0.0468 | 21.34 | 10800 | 0.3607 | 0.2370 |
| 0.0452 | 22.13 | 11200 | 0.3499 | 0.2286 |
| 0.0399 | 22.92 | 11600 | 0.3647 | 0.2282 |
| 0.0393 | 23.72 | 12000 | 0.3638 | 0.2255 |
| 0.0381 | 24.51 | 12400 | 0.3359 | 0.2202 |
| 0.0332 | 25.3 | 12800 | 0.3488 | 0.2177 |
| 0.033 | 26.09 | 13200 | 0.3628 | 0.2175 |
| 0.0311 | 26.88 | 13600 | 0.3695 | 0.2195 |
| 0.0294 | 27.67 | 14000 | 0.3624 | 0.2164 |
| 0.0281 | 28.46 | 14400 | 0.3688 | 0.2113 |
| 0.0274 | 29.25 | 14800 | 0.3596 | 0.2105 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
