---
library_name: transformers
language:
- spa
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Tiny Few Audios - vfranchis
  results: []
---

<!-- 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 Tiny Few Audios - vfranchis

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Few audios 1.0 dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 88.8889

## 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: 10
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0           | 2.5   | 10   | nan             | 88.8889 |
| 0.0           | 5.0   | 20   | nan             | 88.8889 |
| 0.0           | 7.5   | 30   | nan             | 88.8889 |
| 0.0           | 10.0  | 40   | nan             | 88.8889 |
| 0.0           | 12.5  | 50   | nan             | 88.8889 |
| 0.0           | 15.0  | 60   | nan             | 88.8889 |
| 0.0           | 17.5  | 70   | nan             | 88.8889 |
| 0.0           | 20.0  | 80   | nan             | 88.8889 |
| 0.0           | 22.5  | 90   | nan             | 88.8889 |
| 0.0           | 25.0  | 100  | nan             | 88.8889 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1