---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper-event
- generated_from_trainer
datasets:
- asierhv/composite_corpus_eu_v2.1
metrics:
- wer
model-index:
- name: Whisper Tiny Basque
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: asierhv/composite_corpus_eu_v2.1
      type: asierhv/composite_corpus_eu_v2.1
    metrics:
    - name: Wer
      type: wer
      value: 14.849506681653555
---

<!-- 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 Basque

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the asierhv/composite_corpus_eu_v2.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3719
- Wer: 14.8495

## 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: 3.75e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.586         | 0.1   | 1000  | 0.6249          | 34.1639 |
| 0.3145        | 0.2   | 2000  | 0.5048          | 25.2591 |
| 0.225         | 0.3   | 3000  | 0.4839          | 22.0557 |
| 0.3003        | 0.4   | 4000  | 0.4540          | 20.3072 |
| 0.132         | 0.5   | 5000  | 0.4574          | 19.0146 |
| 0.1588        | 0.6   | 6000  | 0.4380          | 17.8219 |
| 0.1841        | 0.7   | 7000  | 0.4395          | 16.6667 |
| 0.143         | 0.8   | 8000  | 0.3719          | 15.4490 |
| 0.0967        | 0.9   | 9000  | 0.3685          | 15.1368 |
| 0.1059        | 1.0   | 10000 | 0.3719          | 14.8495 |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.3.1.dev0
- Tokenizers 0.21.0