---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-basque
  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-basque

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1445
- Wer: 8.2615

## 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-05
- train_batch_size: 96
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1909        | 0.12  | 500   | 0.2820          | 22.5178 |
| 0.1253        | 0.25  | 1000  | 0.2133          | 16.1484 |
| 0.1046        | 0.37  | 1500  | 0.1899          | 12.7139 |
| 0.0874        | 0.5   | 2000  | 0.1793          | 11.4088 |
| 0.0836        | 0.62  | 2500  | 0.1621          | 10.5470 |
| 0.0726        | 0.74  | 3000  | 0.1597          | 10.1161 |
| 0.0707        | 0.87  | 3500  | 0.1498          | 9.4355  |
| 0.0652        | 0.99  | 4000  | 0.1470          | 8.5737  |
| 0.0416        | 1.11  | 4500  | 0.1482          | 8.5925  |
| 0.0415        | 1.24  | 5000  | 0.1490          | 8.6299  |
| 0.0394        | 1.36  | 5500  | 0.1474          | 8.0929  |
| 0.0381        | 1.49  | 6000  | 0.1425          | 8.3489  |
| 0.038         | 1.61  | 6500  | 0.1414          | 8.2990  |
| 0.0333        | 1.73  | 7000  | 0.1391          | 8.2553  |
| 0.0342        | 1.86  | 7500  | 0.1382          | 8.3864  |
| 0.0341        | 1.98  | 8000  | 0.1386          | 8.4301  |
| 0.0196        | 2.11  | 8500  | 0.1447          | 8.1429  |
| 0.0208        | 2.23  | 9000  | 0.1448          | 8.3115  |
| 0.018         | 2.35  | 9500  | 0.1449          | 8.3177  |
| 0.0172        | 2.48  | 10000 | 0.1445          | 8.2615  |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.1.1+cu121
- Datasets 2.8.0
- Tokenizers 0.15.2