metadata
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-mdc-rutoro-asr-3.0.0
results: []
w2v-bert-2.0-mdc-rutoro-asr-3.0.0
This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2288
- Wer: 0.2059
- Cer: 0.0411
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 4.5614 | 1.0 | 84 | 2.8697 | 1.0 | 0.9556 |
| 2.9558 | 2.0 | 168 | 1.1423 | 0.9883 | 0.2675 |
| 1.3943 | 3.0 | 252 | 0.4472 | 0.5657 | 0.1024 |
| 1.0741 | 4.0 | 336 | 0.3785 | 0.4383 | 0.0772 |
| 1.1728 | 5.0 | 420 | 0.3127 | 0.3658 | 0.0654 |
| 0.8781 | 6.0 | 504 | 0.2809 | 0.2998 | 0.0558 |
| 0.8013 | 7.0 | 588 | 0.2611 | 0.2898 | 0.0543 |
| 0.7441 | 8.0 | 672 | 0.2340 | 0.2698 | 0.0513 |
| 0.7162 | 9.0 | 756 | 0.2467 | 0.2529 | 0.0484 |
| 0.7013 | 10.0 | 840 | 0.2505 | 0.2421 | 0.0466 |
| 0.5552 | 11.0 | 924 | 0.2313 | 0.2270 | 0.0433 |
| 0.5324 | 12.0 | 1008 | 0.2374 | 0.2204 | 0.0435 |
| 0.4722 | 13.0 | 1092 | 0.2206 | 0.2189 | 0.0425 |
| 0.638 | 14.0 | 1176 | 0.2197 | 0.2070 | 0.0413 |
| 0.6088 | 15.0 | 1260 | 0.2083 | 0.2129 | 0.0416 |
| 0.4534 | 16.0 | 1344 | 0.2137 | 0.2085 | 0.0412 |
| 0.5218 | 17.0 | 1428 | 0.2246 | 0.2062 | 0.0403 |
| 0.3967 | 18.0 | 1512 | 0.2257 | 0.2021 | 0.0396 |
| 0.6081 | 19.0 | 1596 | 0.2431 | 0.1957 | 0.0398 |
| 0.239 | 20.0 | 1680 | 0.2029 | 0.2023 | 0.0392 |
| 0.3622 | 21.0 | 1764 | 0.2479 | 0.1985 | 0.0395 |
| 0.3429 | 22.0 | 1848 | 0.2335 | 0.1987 | 0.0403 |
| 0.5635 | 23.0 | 1932 | 0.2226 | 0.1982 | 0.0397 |
| 0.4587 | 24.0 | 2016 | 0.2288 | 0.2059 | 0.0411 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.0+cu128
- Datasets 4.4.0
- Tokenizers 0.22.1