---
library_name: transformers
language:
- eu
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- common_voice_21_0_eu
metrics:
- wer
model-index:
- name: Whisper Base Basque
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_21_0_eu
      type: common_voice_21_0_eu
      config: default
      split: test
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 12.788499887287797
---

<!-- 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 Base Basque

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the common_voice_21_0_eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5268
- Wer: 12.7885

## 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: 3.75e-05
- train_batch_size: 128
- eval_batch_size: 64
- 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: 500
- training_steps: 100000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step  | Validation Loss | Wer     |
|:-------------:|:--------:|:-----:|:---------------:|:-------:|
| 0.005         | 22.2222  | 5000  | 0.3503          | 16.5149 |
| 0.0022        | 44.4444  | 10000 | 0.3754          | 15.6124 |
| 0.0015        | 66.6667  | 15000 | 0.3950          | 15.3358 |
| 0.0018        | 88.8889  | 20000 | 0.4129          | 15.5708 |
| 0.0015        | 111.1111 | 25000 | 0.4234          | 15.1078 |
| 0.0004        | 133.3333 | 30000 | 0.4302          | 14.7167 |
| 0.0012        | 155.5556 | 35000 | 0.4466          | 15.0627 |
| 0.0006        | 177.7778 | 40000 | 0.4500          | 15.2569 |
| 0.0           | 200.0    | 45000 | 0.4556          | 13.8705 |
| 0.0           | 222.2222 | 50000 | 0.4783          | 13.3815 |
| 0.0           | 244.4444 | 55000 | 0.5086          | 13.0174 |
| 0.0           | 266.6667 | 60000 | 0.5255          | 12.9151 |
| 0.0           | 288.8889 | 65000 | 0.5255          | 12.8024 |
| 0.0           | 311.1111 | 70000 | 0.5268          | 12.7885 |
| 0.0           | 333.3333 | 75000 | 0.5301          | 12.8058 |
| 0.0           | 355.5556 | 80000 | 0.5325          | 12.8483 |
| 0.0           | 377.7778 | 85000 | 0.5351          | 12.8856 |
| 0.0           | 400.0    | 90000 | 0.5368          | 12.9472 |
| 0.0           | 422.2222 | 95000 | 0.5378          | 12.9662 |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1