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wav2vec2-base-timit-demo-google-colab
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5182
- Wer: 0.3329
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: 8
- eval_batch_size: 8
- 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: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.5177 | 1.0 | 500 | 1.8932 | 0.9837 |
| 0.854 | 2.01 | 1000 | 0.5295 | 0.5266 |
| 0.4205 | 3.01 | 1500 | 0.4299 | 0.4453 |
| 0.2934 | 4.02 | 2000 | 0.3940 | 0.4180 |
| 0.2272 | 5.02 | 2500 | 0.4269 | 0.4149 |
| 0.1856 | 6.02 | 3000 | 0.4277 | 0.4335 |
| 0.1668 | 7.03 | 3500 | 0.4214 | 0.3852 |
| 0.1388 | 8.03 | 4000 | 0.4410 | 0.3805 |
| 0.1254 | 9.04 | 4500 | 0.4152 | 0.3716 |
| 0.1073 | 10.04 | 5000 | 0.4257 | 0.3726 |
| 0.1 | 11.04 | 5500 | 0.4405 | 0.3642 |
| 0.0928 | 12.05 | 6000 | 0.4823 | 0.3708 |
| 0.0829 | 13.05 | 6500 | 0.4636 | 0.3548 |
| 0.0682 | 14.06 | 7000 | 0.4718 | 0.3599 |
| 0.0643 | 15.06 | 7500 | 0.4965 | 0.3583 |
| 0.0609 | 16.06 | 8000 | 0.5279 | 0.3576 |
| 0.0586 | 17.07 | 8500 | 0.4869 | 0.3528 |
| 0.055 | 18.07 | 9000 | 0.4671 | 0.3567 |
| 0.0465 | 19.08 | 9500 | 0.5090 | 0.3508 |
| 0.0432 | 20.08 | 10000 | 0.5024 | 0.3543 |
| 0.0427 | 21.08 | 10500 | 0.4658 | 0.3417 |
| 0.033 | 22.09 | 11000 | 0.5276 | 0.3418 |
| 0.0297 | 23.09 | 11500 | 0.5095 | 0.3415 |
| 0.0317 | 24.1 | 12000 | 0.5061 | 0.3364 |
| 0.0262 | 25.1 | 12500 | 0.4910 | 0.3367 |
| 0.0257 | 26.1 | 13000 | 0.4869 | 0.3331 |
| 0.0237 | 27.11 | 13500 | 0.5023 | 0.3333 |
| 0.0228 | 28.11 | 14000 | 0.5131 | 0.3333 |
| 0.021 | 29.12 | 14500 | 0.5182 | 0.3329 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1
