---
language:
- eu
license: apache-2.0
base_model: zuazo/whisper-base-es
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Base Basque
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_13_0 eu
      type: mozilla-foundation/common_voice_13_0
      config: eu
      split: test
      args: eu
    metrics:
    - name: Wer
      type: wer
      value: 25.752359350317956
---

<!-- 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 [zuazo/whisper-base-es](https://huggingface.co/zuazo/whisper-base-es) on the mozilla-foundation/common_voice_13_0 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5285
- Wer: 25.7524

## 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: 2.5e-05
- train_batch_size: 128
- eval_batch_size: 64
- 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: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0161        | 9.01  | 1000 | 0.4767          | 27.8403 |
| 0.0014        | 19.01 | 2000 | 0.5285          | 25.7524 |
| 0.0007        | 29.0  | 3000 | 0.5603          | 25.8739 |
| 0.0004        | 38.02 | 4000 | 0.5803          | 26.0885 |
| 0.0004        | 48.01 | 5000 | 0.5885          | 26.0885 |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3