---
language:
- eu
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small 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: 14.119648426424725
---

<!-- 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 Small Basque

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_13_0 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2376
- Wer: 14.1196

## 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: 6e-06
- train_batch_size: 4
- eval_batch_size: 8
- 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: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.443         | 0.06  | 500  | 0.5037          | 37.4296 |
| 0.4196        | 0.12  | 1000 | 0.4010          | 28.9137 |
| 0.2823        | 0.19  | 1500 | 0.3453          | 24.6851 |
| 0.2551        | 0.25  | 2000 | 0.3164          | 22.5789 |
| 0.206         | 0.31  | 2500 | 0.2902          | 19.7922 |
| 0.2327        | 0.38  | 3000 | 0.2707          | 18.9356 |
| 0.1416        | 1.03  | 3500 | 0.2566          | 17.6921 |
| 0.0998        | 1.09  | 4000 | 0.2551          | 16.8213 |
| 0.095         | 1.15  | 4500 | 0.2511          | 16.3899 |
| 0.0971        | 1.21  | 5000 | 0.2415          | 15.5393 |
| 0.0964        | 1.28  | 5500 | 0.2336          | 15.1707 |
| 0.072         | 1.34  | 6000 | 0.2353          | 14.7596 |
| 0.0658        | 1.4   | 6500 | 0.2340          | 14.6766 |
| 0.033         | 2.05  | 7000 | 0.2349          | 14.3768 |
| 0.0288        | 2.11  | 7500 | 0.2371          | 14.1865 |
| 0.0352        | 2.18  | 8000 | 0.2376          | 14.1196 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2