---
language:
- es
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Es - Spanish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      args: 'config: es, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 13.333333333333334
---

<!-- 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 - Spanish

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1798
- Wer: 13.3333

## 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: 50
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6172        | 0.1   | 100  | 0.6200          | 107.3958 |
| 0.2709        | 0.21  | 200  | 0.3492          | 67.0833  |
| 0.2839        | 0.31  | 300  | 0.2959          | 40.7292  |
| 0.2876        | 0.41  | 400  | 0.2766          | 29.5833  |
| 0.2296        | 0.52  | 500  | 0.2375          | 17.3958  |
| 0.2649        | 0.62  | 600  | 0.2102          | 15.3125  |
| 0.2644        | 0.72  | 700  | 0.1957          | 17.3958  |
| 0.2384        | 0.82  | 800  | 0.1886          | 13.7500  |
| 0.2325        | 0.93  | 900  | 0.1811          | 13.6458  |
| 0.1374        | 1.03  | 1000 | 0.1798          | 13.3333  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0