---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- automatic-speech-recognition,whisper
- generated_from_trainer
metrics:
- wer
model-index:
- name: GAL500
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Enpas/GALKG
      type: Enpas/GALKG
    metrics:
    - name: Wer
      type: wer
      value: 25.21137586471945
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# GAL500

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Enpas/GALKG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2507
- Wer: 25.2114

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5194        | 0.3199 | 1000 | 0.4919          | 45.8570 |
| 0.4237        | 0.6398 | 2000 | 0.3681          | 37.4251 |
| 0.349         | 0.9597 | 3000 | 0.3047          | 30.5457 |
| 0.2235        | 1.2796 | 4000 | 0.2758          | 27.5404 |
| 0.188         | 1.5995 | 5000 | 0.2507          | 25.2114 |


### Framework versions

- Transformers 4.54.1
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.1