---
language:
- spa
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- CIEMPIESS
metrics:
- wer
model-index:
- name: Whisper Small Spanish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: CIEMPIESS
      type: CIEMPIESS
      args: 'config: spa, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.38445504655148455
---

<!-- 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 Spanish

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the CIEMPIESS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0152
- Wer: 0.3845

## 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.2277        | 0.4484 | 100  | 0.2420          | 9.5187 |
| 0.2788        | 0.8969 | 200  | 0.1965          | 7.9300 |
| 0.1799        | 1.3453 | 300  | 0.1541          | 6.9804 |
| 0.158         | 1.7937 | 400  | 0.1121          | 5.4762 |
| 0.0926        | 2.2422 | 500  | 0.0810          | 4.1792 |
| 0.0912        | 2.6906 | 600  | 0.0584          | 3.7438 |
| 0.0451        | 3.1390 | 700  | 0.0364          | 2.4318 |
| 0.0416        | 3.5874 | 800  | 0.0261          | 1.3271 |
| 0.0312        | 4.0359 | 900  | 0.0178          | 0.4736 |
| 0.015         | 4.4843 | 1000 | 0.0152          | 0.3845 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1