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wav2vec2-random
This model is a fine-tuned version of patrickvonplaten/wav2vec2-base-random on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:
- Loss: 3.1593
- Wer: 0.8364
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: 0.0001
- train_batch_size: 32
- 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: 1000
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.9043 | 0.69 | 100 | 2.9683 | 1.0 |
| 2.8537 | 1.38 | 200 | 2.9281 | 0.9997 |
| 2.7803 | 2.07 | 300 | 2.7330 | 0.9999 |
| 2.6806 | 2.76 | 400 | 2.5792 | 1.0 |
| 2.4136 | 3.45 | 500 | 2.4327 | 0.9948 |
| 2.1682 | 4.14 | 600 | 2.3508 | 0.9877 |
| 2.2577 | 4.83 | 700 | 2.2176 | 0.9773 |
| 2.355 | 5.52 | 800 | 2.1753 | 0.9542 |
| 1.8588 | 6.21 | 900 | 2.0650 | 0.8851 |
| 1.6831 | 6.9 | 1000 | 2.0109 | 0.8618 |
| 1.888 | 7.59 | 1100 | 1.9660 | 0.8418 |
| 2.0066 | 8.28 | 1200 | 1.9847 | 0.8531 |
| 1.7044 | 8.97 | 1300 | 1.9760 | 0.8527 |
| 1.3168 | 9.66 | 1400 | 2.0708 | 0.8327 |
| 1.2143 | 10.34 | 1500 | 2.0601 | 0.8419 |
| 1.6189 | 11.03 | 1600 | 2.0960 | 0.8299 |
| 1.13 | 11.72 | 1700 | 2.2540 | 0.8408 |
| 0.8001 | 12.41 | 1800 | 2.4260 | 0.8306 |
| 0.7769 | 13.1 | 1900 | 2.4182 | 0.8445 |
| 1.2165 | 13.79 | 2000 | 2.3666 | 0.8284 |
| 0.8026 | 14.48 | 2100 | 2.7118 | 0.8662 |
| 0.5148 | 15.17 | 2200 | 2.7957 | 0.8526 |
| 0.4921 | 15.86 | 2300 | 2.8244 | 0.8346 |
| 0.7629 | 16.55 | 2400 | 2.8944 | 0.8370 |
| 0.5762 | 17.24 | 2500 | 3.0335 | 0.8367 |
| 0.4076 | 17.93 | 2600 | 3.0776 | 0.8358 |
| 0.3395 | 18.62 | 2700 | 3.1572 | 0.8261 |
| 0.4862 | 19.31 | 2800 | 3.1319 | 0.8414 |
| 0.5061 | 20.0 | 2900 | 3.1593 | 0.8364 |
Framework versions
- Transformers 4.12.0.dev0
- Pytorch 1.8.1
- Datasets 1.14.1.dev0
- Tokenizers 0.10.3
