---
language:
- es
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- arturoapio/MadeUpWords
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: Whisper Small es - Galilei
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice Made up words
      type: arturoapio/MadeUpWords
      args: 'config: es, split: test'
    metrics:
    - type: wer
      value: 7.2727272727272725
      name: Wer
---

<!-- 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 es - Galilei

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice Made up words dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 7.2727

## 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: 16
- 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.0           | 71.43  | 1000 | 0.0000          | 5.4545 |
| 0.0           | 142.86 | 2000 | 0.0000          | 9.0909 |
| 0.0           | 214.29 | 3000 | 0.0000          | 7.2727 |
| 0.0           | 285.71 | 4000 | 0.0000          | 7.2727 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1