---
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 1000 Diverse 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 1000 Diverse Audios - vfranchis

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the 1000 diverse audios 1.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1835
- Wer: 42.9577

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 25
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 3.7684        | 0.4425 | 25   | 2.2485          | 135.5131 |
| 1.5347        | 0.8850 | 50   | 0.9286          | 75.5533  |
| 0.8425        | 1.3274 | 75   | 0.5561          | 56.4386  |
| 0.5722        | 1.7699 | 100  | 0.4103          | 43.4608  |
| 0.3867        | 2.2124 | 125  | 0.3423          | 40.5433  |
| 0.3107        | 2.6549 | 150  | 0.2967          | 51.0060  |
| 0.2931        | 3.0973 | 175  | 0.2656          | 78.8732  |
| 0.2031        | 3.5398 | 200  | 0.2421          | 57.8471  |
| 0.2004        | 3.9823 | 225  | 0.2305          | 51.8109  |
| 0.1254        | 4.4248 | 250  | 0.2198          | 22.4346  |
| 0.1332        | 4.8673 | 275  | 0.2070          | 22.2334  |
| 0.1089        | 5.3097 | 300  | 0.2049          | 51.4085  |
| 0.0627        | 5.7522 | 325  | 0.1988          | 28.5714  |
| 0.0959        | 6.1947 | 350  | 0.1948          | 31.6901  |
| 0.0794        | 6.6372 | 375  | 0.1910          | 28.8732  |
| 0.0696        | 7.0796 | 400  | 0.1879          | 43.5614  |
| 0.0458        | 7.5221 | 425  | 0.1861          | 43.4608  |
| 0.0524        | 7.9646 | 450  | 0.1841          | 53.5211  |
| 0.0453        | 8.4071 | 475  | 0.1832          | 40.4427  |
| 0.0485        | 8.8496 | 500  | 0.1835          | 42.9577  |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1