---
library_name: transformers
language:
- spa
license: apache-2.0
base_model: rasel35/whisper-base-es-medical-terms
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Pre Tuned 300 Audios - Nacho v3.0
  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 Pre Tuned 300 Audios - Nacho v3.0

This model is a fine-tuned version of [rasel35/whisper-base-es-medical-terms](https://huggingface.co/rasel35/whisper-base-es-medical-terms) on the 300 audios 1.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3444
- Wer: 16.1793

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use 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: 50
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.8732        | 1.0    | 18   | 1.1907          | 60.6238 |
| 0.676         | 2.0    | 36   | 0.4489          | 21.0526 |
| 0.2633        | 3.0    | 54   | 0.4061          | 17.9337 |
| 0.132         | 4.0    | 72   | 0.3804          | 17.9337 |
| 0.0802        | 5.0    | 90   | 0.3507          | 41.7154 |
| 0.0498        | 6.0    | 108  | 0.3660          | 18.5185 |
| 0.036         | 7.0    | 126  | 0.3614          | 17.3489 |
| 0.0213        | 8.0    | 144  | 0.3329          | 15.9844 |
| 0.0152        | 9.0    | 162  | 0.3453          | 15.7895 |
| 0.0042        | 9.4507 | 170  | 0.3444          | 16.1793 |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.21.0