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wav2vec2-demo-M01
This model is a fine-tuned version of yip-i/uaspeech-pretrained on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.7099
- Wer: 1.4021
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 |
|---|---|---|---|---|
| 7.3895 | 0.9 | 500 | 2.9817 | 1.0007 |
| 3.0164 | 1.8 | 1000 | 2.9513 | 1.2954 |
| 3.0307 | 2.7 | 1500 | 2.8709 | 1.3286 |
| 3.1314 | 3.6 | 2000 | 2.8754 | 1.0 |
| 3.0395 | 4.5 | 2500 | 2.9289 | 1.0 |
| 3.2647 | 5.41 | 3000 | 2.8134 | 1.0014 |
| 2.9821 | 6.31 | 3500 | 2.8370 | 1.3901 |
| 2.9262 | 7.21 | 4000 | 2.8731 | 1.3809 |
| 2.9982 | 8.11 | 4500 | 4.4794 | 1.3958 |
| 3.0807 | 9.01 | 5000 | 2.8268 | 1.3951 |
| 2.8873 | 9.91 | 5500 | 2.8014 | 1.5336 |
| 2.8755 | 10.81 | 6000 | 2.8010 | 1.3873 |
| 3.2618 | 11.71 | 6500 | 3.1033 | 1.3463 |
| 3.0063 | 12.61 | 7000 | 2.7906 | 1.3753 |
| 2.8481 | 13.51 | 7500 | 2.7874 | 1.3837 |
| 2.876 | 14.41 | 8000 | 2.8239 | 1.0636 |
| 2.8966 | 15.32 | 8500 | 2.7753 | 1.3915 |
| 2.8839 | 16.22 | 9000 | 2.7874 | 1.3223 |
| 2.8351 | 17.12 | 9500 | 2.7755 | 1.3915 |
| 2.8185 | 18.02 | 10000 | 2.7600 | 1.3908 |
| 2.8193 | 18.92 | 10500 | 2.7542 | 1.3915 |
| 2.8023 | 19.82 | 11000 | 2.7528 | 1.3915 |
| 2.7934 | 20.72 | 11500 | 2.7406 | 1.3915 |
| 2.8043 | 21.62 | 12000 | 2.7419 | 1.3915 |
| 2.7941 | 22.52 | 12500 | 2.7407 | 1.3915 |
| 2.7854 | 23.42 | 13000 | 2.7277 | 1.3915 |
| 2.7924 | 24.32 | 13500 | 2.7279 | 1.3915 |
| 2.7644 | 25.23 | 14000 | 2.7217 | 1.3915 |
| 2.7703 | 26.13 | 14500 | 2.7273 | 1.5032 |
| 2.7821 | 27.03 | 15000 | 2.7265 | 1.3915 |
| 2.7632 | 27.93 | 15500 | 2.7154 | 1.3915 |
| 2.749 | 28.83 | 16000 | 2.7125 | 1.3958 |
| 2.7515 | 29.73 | 16500 | 2.7099 | 1.4021 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 1.18.3
- Tokenizers 0.13.2
