---
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: 100.0

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 2.5797        | 3.0769  | 10   | nan             | 83.3333 |
| 1.45          | 6.1538  | 20   | nan             | 58.3333 |
| 0.5973        | 9.2308  | 30   | nan             | 33.3333 |
| 0.234         | 12.3077 | 40   | nan             | 33.3333 |
| 0.1089        | 15.3846 | 50   | nan             | 25.0    |
| 0.052         | 18.4615 | 60   | nan             | 33.3333 |
| 0.0425        | 21.5385 | 70   | nan             | 33.3333 |
| 0.2025        | 24.6154 | 80   | nan             | 50.0    |
| 1.957         | 27.6923 | 90   | nan             | 100.0   |
| 6.8512        | 30.7692 | 100  | nan             | 100.0   |


### Framework versions

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