---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-small
  results: []
---

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

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Hanhpt23/MultiMed dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7193
- Wer: 19.9744
- Cer: 14.0186

## 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: 0.0001
- train_batch_size: 8
- 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: 100
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.6396        | 1.0   | 4626  | 0.7132          | 31.7615 | 22.7290 |
| 0.3406        | 2.0   | 9252  | 0.6568          | 25.4179 | 18.0443 |
| 0.1281        | 3.0   | 13878 | 0.6780          | 22.2623 | 15.5534 |
| 0.026         | 4.0   | 18504 | 0.7193          | 19.9744 | 14.0186 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1