---
language:
- es
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper tiny es - m1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fleurs
      type: google/fleurs
      config: es_419
      split: None
      args: 'config: es_419, split: test, train'
    metrics:
    - name: Wer
      type: wer
      value: 18.93646290086837
---

<!-- 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 es - m1

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4496
- Wer: 18.9365

## 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: 250
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.2138        | 1.4286 | 250  | 0.4507          | 20.0241 |
| 0.9388        | 2.8571 | 500  | 0.4302          | 18.4378 |
| 0.8286        | 4.2857 | 750  | 0.4378          | 18.7043 |
| 0.7681        | 5.7143 | 1000 | 0.4426          | 18.7645 |
| 0.6715        | 7.1429 | 1250 | 0.4477          | 18.8763 |
| 0.5874        | 8.5714 | 1500 | 0.4496          | 18.9365 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1