transformers pytorch whisper automatic-speech-recognition whisper-event generated_from_trainer eu dataset:mozilla-foundation/common_voice_13_0 base_model:zuazo/whisper-small-es license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- eu
license: apache-2.0
base_model: zuazo/whisper-small-es
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: 19.76386244886387
---

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# Whisper Small Basque

This model is a fine-tuned version of [zuazo/whisper-small-es](https://huggingface.co/zuazo/whisper-small-es) on the mozilla-foundation/common_voice_13_0 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4464
- Wer: 19.7639

## 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: 64
- eval_batch_size: 32
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.047         | 4.04  | 1000 | 0.3386          | 21.7425 |
| 0.0043        | 9.03  | 2000 | 0.3903          | 20.1770 |
| 0.0011        | 14.02 | 3000 | 0.4209          | 19.7801 |
| 0.0008        | 19.02 | 4000 | 0.4381          | 20.0170 |
| 0.0006        | 24.01 | 5000 | 0.4464          | 19.7639 |


### Framework versions

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