---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-basque
  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. -->

# whisper-base-basque

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2498
- Wer: 62.1644

## 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: 1e-05
- train_batch_size: 192
- eval_batch_size: 96
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer      |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4078        | 0.25  | 500   | 0.5613          | 136.6055 |
| 0.2533        | 0.5   | 1000  | 0.3973          | 105.6700 |
| 0.1994        | 0.74  | 1500  | 0.3350          | 73.1485  |
| 0.1723        | 0.99  | 2000  | 0.3101          | 55.7387  |
| 0.1403        | 1.24  | 2500  | 0.2895          | 49.8689  |
| 0.1318        | 1.49  | 3000  | 0.2800          | 70.4321  |
| 0.1279        | 1.73  | 3500  | 0.2711          | 80.4296  |
| 0.1192        | 1.98  | 4000  | 0.2667          | 60.5533  |
| 0.104         | 2.23  | 4500  | 0.2605          | 54.0402  |
| 0.0986        | 2.48  | 5000  | 0.2601          | 53.4158  |
| 0.0929        | 2.73  | 5500  | 0.2539          | 61.0653  |
| 0.0971        | 2.97  | 6000  | 0.2521          | 45.2104  |
| 0.0806        | 3.22  | 6500  | 0.2526          | 51.5736  |
| 0.0812        | 3.47  | 7000  | 0.2509          | 53.9903  |
| 0.0817        | 3.72  | 7500  | 0.2498          | 56.8440  |
| 0.0799        | 3.96  | 8000  | 0.2511          | 65.1305  |
| 0.0723        | 4.21  | 8500  | 0.2500          | 55.6326  |
| 0.0724        | 4.46  | 9000  | 0.2498          | 60.2910  |
| 0.0707        | 4.71  | 9500  | 0.2501          | 59.5854  |
| 0.0685        | 4.96  | 10000 | 0.2498          | 62.1644  |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.1.1+cu121
- Datasets 2.8.0
- Tokenizers 0.15.2