uaspeech-foundation-fintuned
- Loss: 2.5324
- Wer: 1.2855
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: 4
- 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 |
|---|---|---|---|---|
| 41.2984 | 0.7 | 500 | 2.8954 | 1.0 |
| 3.0227 | 1.4 | 1000 | 2.8232 | 1.0042 |
| 2.8283 | 2.11 | 1500 | 2.6291 | 1.0309 |
| 2.5552 | 2.81 | 2000 | 2.2593 | 1.9170 |
| 2.1714 | 3.51 | 2500 | 1.9586 | 1.9142 |
| 1.8537 | 4.21 | 3000 | 1.5725 | 1.8579 |
| 1.6087 | 4.92 | 3500 | 1.2772 | 1.7426 |
| 1.3108 | 5.62 | 4000 | 1.2792 | 1.6751 |
| 1.1652 | 6.32 | 4500 | 1.4565 | 1.6174 |
| 1.0113 | 7.02 | 5000 | 1.1906 | 1.5626 |
| 0.925 | 7.72 | 5500 | 1.4491 | 1.5260 |
| 0.8183 | 8.43 | 6000 | 1.3712 | 1.5387 |
| 0.7118 | 9.13 | 6500 | 1.4713 | 1.4866 |
| 0.6959 | 9.83 | 7000 | 1.3336 | 1.4318 |
| 0.6146 | 10.53 | 7500 | 1.3690 | 1.4177 |
| 0.5655 | 11.24 | 8000 | 1.3789 | 1.4135 |
| 0.4969 | 11.94 | 8500 | 1.5476 | 1.3966 |
| 0.4705 | 12.64 | 9000 | 1.9062 | 1.3797 |
| 0.4387 | 13.34 | 9500 | 1.2711 | 1.3924 |
| 0.4115 | 14.04 | 10000 | 1.6318 | 1.3769 |
| 0.3695 | 14.75 | 10500 | 1.5119 | 1.3755 |
| 0.377 | 15.45 | 11000 | 1.6637 | 1.3812 |
| 0.3788 | 16.15 | 11500 | 1.6636 | 1.3699 |
| 0.3396 | 16.85 | 12000 | 1.6572 | 1.3418 |
| 0.3047 | 17.56 | 12500 | 1.4740 | 1.3361 |
| 0.2804 | 18.26 | 13000 | 2.0885 | 1.3249 |
| 0.2995 | 18.96 | 13500 | 1.9536 | 1.3235 |
| 0.2628 | 19.66 | 14000 | 1.7736 | 1.3179 |
| 0.2703 | 20.37 | 14500 | 2.0018 | 1.3291 |
| 0.2335 | 21.07 | 15000 | 1.7962 | 1.3221 |
| 0.2068 | 21.77 | 15500 | 2.3187 | 1.3136 |
| 0.2311 | 22.47 | 16000 | 2.4853 | 1.3291 |
| 0.2491 | 23.17 | 16500 | 2.1901 | 1.3024 |
| 0.1836 | 23.88 | 17000 | 2.4344 | 1.2911 |
| 0.1823 | 24.58 | 17500 | 2.3705 | 1.3066 |
| 0.1575 | 25.28 | 18000 | 2.1864 | 1.2897 |
| 0.1451 | 25.98 | 18500 | 2.4216 | 1.2883 |
| 0.1502 | 26.69 | 19000 | 2.1780 | 1.2855 |
| 0.1392 | 27.39 | 19500 | 2.4009 | 1.2925 |
| 0.1609 | 28.09 | 20000 | 2.4250 | 1.2982 |
| 0.1066 | 28.79 | 20500 | 2.4433 | 1.2897 |
| 0.1514 | 29.49 | 21000 | 2.5063 | 1.2855 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 1.18.3
- Tokenizers 0.13.2
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