---
language:
- eu
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Medium Basque
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_0 eu
      type: mozilla-foundation/common_voice_16_0
      config: eu
      split: test
      args: eu
    metrics:
    - name: Wer
      type: wer
      value: 9.188591686749389
---

<!-- 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 Medium Basque

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_16_0 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1503
- Wer: 9.1886

## 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: 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4647        | 0.06  | 500  | 0.4529          | 34.2140 |
| 0.3163        | 0.12  | 1000 | 0.3516          | 26.0232 |
| 0.3232        | 0.19  | 1500 | 0.2996          | 21.1825 |
| 0.266         | 0.25  | 2000 | 0.2686          | 18.5126 |
| 0.2383        | 0.31  | 2500 | 0.2489          | 16.9412 |
| 0.1916        | 0.38  | 3000 | 0.2233          | 15.2831 |
| 0.2009        | 0.44  | 3500 | 0.2134          | 14.1419 |
| 0.2014        | 0.5   | 4000 | 0.2015          | 13.6579 |
| 0.1964        | 0.56  | 4500 | 0.1853          | 12.0198 |
| 0.1758        | 0.62  | 5000 | 0.1796          | 11.4651 |
| 0.2067        | 0.69  | 5500 | 0.1679          | 10.7989 |
| 0.213         | 0.75  | 6000 | 0.1618          | 10.3139 |
| 0.1272        | 1.03  | 6500 | 0.1551          | 9.8687  |
| 0.0744        | 1.09  | 7000 | 0.1534          | 9.5172  |
| 0.0726        | 1.16  | 7500 | 0.1518          | 9.3240  |
| 0.0627        | 1.22  | 8000 | 0.1503          | 9.1886  |


### Framework versions

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