---
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
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# 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