---
license: mit
base_model: cportoca/CS224S_Quechua_Project
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: CS224S_Quechua_Project
  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

This model is a fine-tuned version of [cportoca/CS224S_Quechua_Project](https://huggingface.co/cportoca/CS224S_Quechua_Project) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0264
- Wer: 0.6160

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4218        | 0.625 | 45   | 1.2929          | 0.8437 |
| 0.4233        | 1.25  | 90   | 1.3785          | 0.8580 |
| 0.4098        | 1.875 | 135  | 1.2656          | 0.8277 |
| 0.4212        | 2.5   | 180  | 1.1368          | 0.7781 |
| 0.3174        | 3.125 | 225  | 1.1210          | 0.8134 |
| 0.2819        | 3.75  | 270  | 1.0151          | 0.7221 |
| 0.2226        | 4.375 | 315  | 1.0450          | 0.7723 |
| 0.2152        | 5.0   | 360  | 1.0446          | 0.7100 |
| 0.2023        | 5.625 | 405  | 1.0544          | 0.7339 |
| 0.1547        | 6.25  | 450  | 1.0352          | 0.6932 |
| 0.1358        | 6.875 | 495  | 1.0490          | 0.6562 |
| 0.1229        | 7.5   | 540  | 1.0429          | 0.6500 |
| 0.079         | 8.125 | 585  | 0.9882          | 0.6532 |
| 0.0896        | 8.75  | 630  | 1.0109          | 0.6322 |
| 0.052         | 9.375 | 675  | 1.0006          | 0.6275 |
| 0.0515        | 10.0  | 720  | 1.0264          | 0.6160 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1