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exp21-uaspeech-foundation
This model is a fine-tuned version of yongjian/wav2vec2-large-a on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4644
- Wer: 1.2633
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 |
|---|---|---|---|---|
| 27.1608 | 0.67 | 500 | 3.0053 | 1.0 |
| 3.2225 | 1.35 | 1000 | 2.8180 | 1.0 |
| 2.7882 | 2.02 | 1500 | 2.5589 | 1.3125 |
| 2.4911 | 2.7 | 2000 | 2.1110 | 1.9129 |
| 2.1921 | 3.37 | 2500 | 1.8404 | 1.8504 |
| 1.833 | 4.04 | 3000 | 1.5873 | 1.8030 |
| 1.51 | 4.72 | 3500 | 1.3015 | 1.6951 |
| 1.2721 | 5.39 | 4000 | 1.2160 | 1.6136 |
| 1.1451 | 6.06 | 4500 | 1.4102 | 1.6212 |
| 0.9631 | 6.74 | 5000 | 1.1730 | 1.5587 |
| 0.9608 | 7.41 | 5500 | 1.4232 | 1.5473 |
| 0.8454 | 8.09 | 6000 | 1.3427 | 1.4830 |
| 0.7377 | 8.76 | 6500 | 1.3691 | 1.4716 |
| 0.6465 | 9.43 | 7000 | 1.4927 | 1.4489 |
| 0.6538 | 10.11 | 7500 | 1.3825 | 1.4072 |
| 0.591 | 10.78 | 8000 | 1.3166 | 1.4186 |
| 0.5476 | 11.46 | 8500 | 1.2636 | 1.3826 |
| 0.515 | 12.13 | 9000 | 1.4861 | 1.4072 |
| 0.5027 | 12.8 | 9500 | 1.7483 | 1.3826 |
| 0.4714 | 13.48 | 10000 | 1.4656 | 1.3598 |
| 0.4506 | 14.15 | 10500 | 1.4430 | 1.3693 |
| 0.3944 | 14.82 | 11000 | 2.0191 | 1.3352 |
| 0.3604 | 15.5 | 11500 | 1.6739 | 1.3428 |
| 0.3533 | 16.17 | 12000 | 1.7428 | 1.3314 |
| 0.3345 | 16.85 | 12500 | 1.6851 | 1.3277 |
| 0.3133 | 17.52 | 13000 | 1.8589 | 1.3106 |
| 0.2772 | 18.19 | 13500 | 2.0114 | 1.2955 |
| 0.2789 | 18.87 | 14000 | 2.0333 | 1.2879 |
| 0.2361 | 19.54 | 14500 | 2.6048 | 1.3030 |
| 0.2406 | 20.22 | 15000 | 2.8444 | 1.2841 |
| 0.2673 | 20.89 | 15500 | 1.9573 | 1.2746 |
| 0.2067 | 21.56 | 16000 | 2.1780 | 1.2936 |
| 0.2281 | 22.24 | 16500 | 2.2629 | 1.2765 |
| 0.1735 | 22.91 | 17000 | 2.2492 | 1.2822 |
| 0.1902 | 23.58 | 17500 | 2.0317 | 1.2803 |
| 0.1659 | 24.26 | 18000 | 2.0658 | 1.2652 |
| 0.1746 | 24.93 | 18500 | 2.2515 | 1.2708 |
| 0.1409 | 25.61 | 19000 | 2.1689 | 1.2595 |
| 0.1461 | 26.28 | 19500 | 2.2441 | 1.2614 |
| 0.1699 | 26.95 | 20000 | 2.1327 | 1.2633 |
| 0.1378 | 27.63 | 20500 | 2.1795 | 1.2670 |
| 0.1108 | 28.3 | 21000 | 2.4057 | 1.2576 |
| 0.1505 | 28.98 | 21500 | 2.4389 | 1.2595 |
| 0.1492 | 29.65 | 22000 | 2.4644 | 1.2633 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 1.18.3
- Tokenizers 0.13.2
