---
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 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 Audios - vfranchis

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the 1000 audios 1.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5691
- Wer: 30.7692

## 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: 300
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.4694        | 0.4   | 25   | 1.0082          | 38.4615 |
| 0.2677        | 0.8   | 50   | 0.7480          | 46.1538 |
| 0.1034        | 1.2   | 75   | 0.6340          | 46.1538 |
| 0.0672        | 1.6   | 100  | 0.6319          | 46.1538 |
| 0.0547        | 2.0   | 125  | 0.5773          | 30.7692 |
| 0.0299        | 2.4   | 150  | 0.5612          | 30.7692 |
| 0.022         | 2.8   | 175  | 0.5784          | 30.7692 |
| 0.0218        | 3.2   | 200  | 0.5702          | 30.7692 |
| 0.0127        | 3.6   | 225  | 0.5721          | 30.7692 |
| 0.013         | 4.0   | 250  | 0.5554          | 30.7692 |
| 0.0084        | 4.4   | 275  | 0.5680          | 30.7692 |
| 0.0102        | 4.8   | 300  | 0.5691          | 30.7692 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1