CS224S_Quechua_Project_Bilingual
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: 0.2367
- Wer: 0.2585
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 70
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.2273 | 0.3628 | 600 | 0.6478 | 0.6345 |
| 0.5989 | 0.7255 | 1200 | 0.4562 | 0.4218 |
| 0.4847 | 1.0883 | 1800 | 0.3781 | 0.3914 |
| 0.4599 | 1.4510 | 2400 | 0.3657 | 0.3400 |
| 0.3462 | 1.8138 | 3000 | 0.3296 | 0.3185 |
| 0.3738 | 2.1765 | 3600 | 0.2808 | 0.2975 |
| 0.2969 | 2.5393 | 4200 | 0.2856 | 0.2877 |
| 0.3985 | 2.9021 | 4800 | 0.2728 | 0.2889 |
| 0.2507 | 3.2648 | 5400 | 0.2676 | 0.2732 |
| 0.284 | 3.6276 | 6000 | 0.2539 | 0.2553 |
| 0.317 | 3.9903 | 6600 | 0.2359 | 0.2496 |
| 0.1526 | 4.3531 | 7200 | 0.2444 | 0.2609 |
| 0.1813 | 4.7158 | 7800 | 0.2367 | 0.2585 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1