| | --- |
| | license: mit |
| | base_model: facebook/w2v-bert-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: CS224S_Quechua_Project_Bilingual |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # CS224S_Quechua_Project_Bilingual |
| | |
| | This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/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 |
| | |
