w2v-bert-cv-grain-lg_both
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 16.2243
- Wer: 1.0
- Cer: 1.0
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.4609 | 1.0 | 5406 | 0.1400 | 0.1423 | 0.0296 |
| 0.2829 | 2.0 | 10812 | 0.1133 | 0.0968 | 0.0213 |
| 0.2369 | 3.0 | 16218 | 0.1033 | 0.0883 | 0.0193 |
| 0.2106 | 4.0 | 21624 | 0.0848 | 0.0681 | 0.0162 |
| 0.197 | 5.0 | 27030 | 0.0871 | 0.0681 | 0.0159 |
| 0.2459 | 6.0 | 32436 | 0.1335 | 0.1022 | 0.0203 |
| 0.3563 | 7.0 | 37842 | 0.1809 | 0.1254 | 0.0267 |
| 0.6033 | 8.0 | 43248 | 0.5575 | 0.7032 | 0.1768 |
| 4.656 | 9.0 | 48654 | 16.9063 | 0.9980 | 0.9837 |
| 10.5595 | 10.0 | 54060 | 12.4706 | 1.0 | 1.0 |
| 17.1148 | 11.0 | 59466 | 16.2280 | 1.0 | 1.0 |
| 17.4223 | 12.0 | 64872 | 16.2273 | 1.0 | 1.0 |
| 17.4172 | 13.0 | 70278 | 16.2222 | 1.0 | 1.0 |
| 17.4159 | 14.0 | 75684 | 16.2243 | 1.0 | 1.0 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1