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wav2vec2-demo-M02-2
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2709
- Wer: 1.0860
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 23.4917 | 0.91 | 500 | 3.2945 | 1.0 |
| 3.4102 | 1.81 | 1000 | 3.1814 | 1.0 |
| 2.9438 | 2.72 | 1500 | 2.7858 | 1.0 |
| 2.6698 | 3.62 | 2000 | 2.4745 | 1.0035 |
| 1.9542 | 4.53 | 2500 | 1.8675 | 1.3745 |
| 1.2737 | 5.43 | 3000 | 1.6459 | 1.3703 |
| 0.9748 | 6.34 | 3500 | 1.8406 | 1.3037 |
| 0.7696 | 7.25 | 4000 | 1.5086 | 1.2476 |
| 0.6396 | 8.15 | 4500 | 1.8280 | 1.2476 |
| 0.558 | 9.06 | 5000 | 1.7680 | 1.2247 |
| 0.4865 | 9.96 | 5500 | 1.8210 | 1.2309 |
| 0.4244 | 10.87 | 6000 | 1.7910 | 1.1775 |
| 0.3898 | 11.78 | 6500 | 1.8021 | 1.1831 |
| 0.3456 | 12.68 | 7000 | 1.7746 | 1.1456 |
| 0.3349 | 13.59 | 7500 | 1.8969 | 1.1519 |
| 0.3233 | 14.49 | 8000 | 1.7402 | 1.1234 |
| 0.3046 | 15.4 | 8500 | 1.8585 | 1.1429 |
| 0.2622 | 16.3 | 9000 | 1.6687 | 1.0950 |
| 0.2593 | 17.21 | 9500 | 1.8192 | 1.1144 |
| 0.2541 | 18.12 | 10000 | 1.8665 | 1.1110 |
| 0.2098 | 19.02 | 10500 | 1.9996 | 1.1186 |
| 0.2192 | 19.93 | 11000 | 2.0346 | 1.1040 |
| 0.1934 | 20.83 | 11500 | 2.1924 | 1.1012 |
| 0.2034 | 21.74 | 12000 | 1.8060 | 1.0929 |
| 0.1857 | 22.64 | 12500 | 2.0334 | 1.0798 |
| 0.1819 | 23.55 | 13000 | 2.1223 | 1.1040 |
| 0.1621 | 24.46 | 13500 | 2.1795 | 1.0957 |
| 0.1548 | 25.36 | 14000 | 2.1545 | 1.1089 |
| 0.1512 | 26.27 | 14500 | 2.2707 | 1.1186 |
| 0.1472 | 27.17 | 15000 | 2.1698 | 1.0888 |
| 0.1296 | 28.08 | 15500 | 2.2496 | 1.0867 |
| 0.1312 | 28.99 | 16000 | 2.2969 | 1.0881 |
| 0.1331 | 29.89 | 16500 | 2.2709 | 1.0860 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 1.18.3
- Tokenizers 0.13.2
