---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small En Medimix
  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 Small En Medimix

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the 500 pes_colab 10.6 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4537
- Wer: 10.6667

## 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-06
- 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: 200
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0384        | 1.0   | 25   | 0.4705          | 12.2222 |
| 0.0375        | 2.0   | 50   | 0.4689          | 12.0    |
| 0.0332        | 3.0   | 75   | 0.4666          | 11.0370 |
| 0.0293        | 4.0   | 100  | 0.4636          | 11.1111 |
| 0.0242        | 5.0   | 125  | 0.4612          | 11.0370 |
| 0.0197        | 6.0   | 150  | 0.4586          | 10.9630 |
| 0.0152        | 7.0   | 175  | 0.4555          | 10.7407 |
| 0.0116        | 8.0   | 200  | 0.4537          | 10.6667 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0