---
library_name: transformers
license: apache-2.0
base_model: luiz-milare/whisper-medium-medical-v4
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-medical-refined-v1
  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-medium-medical-refined-v1

This model is a fine-tuned version of [luiz-milare/whisper-medium-medical-v4](https://huggingface.co/luiz-milare/whisper-medium-medical-v4) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2670
- Wer: 20.5464

## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.109         | 0.4980 | 141  | 0.2438          | 19.8619 |
| 0.1185        | 0.9960 | 282  | 0.2499          | 20.6108 |
| 0.1186        | 1.4909 | 423  | 0.2533          | 21.2426 |
| 0.0984        | 1.9890 | 564  | 0.2529          | 21.1315 |
| 0.0734        | 2.4839 | 705  | 0.2710          | 20.5991 |
| 0.077         | 2.9819 | 846  | 0.2670          | 20.5464 |


### Framework versions

- Transformers 4.52.0
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2