---
language:
- eu
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Small Basque
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_1 eu
      type: mozilla-foundation/common_voice_16_1
      config: eu
      split: test
      args: eu
    metrics:
    - name: Wer
      type: wer
      value: 12.73741597623886
---

<!-- 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 Basque

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_16_1 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3785
- Wer: 12.7374

## 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: 64
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 40000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.0153        | 10.03  | 1000  | 0.2690          | 15.3119 |
| 0.0029        | 20.05  | 2000  | 0.3132          | 15.0334 |
| 0.0018        | 30.08  | 3000  | 0.3312          | 14.6113 |
| 0.0009        | 40.1   | 4000  | 0.3375          | 14.0916 |
| 0.0037        | 50.13  | 5000  | 0.3306          | 14.3241 |
| 0.0002        | 60.15  | 6000  | 0.3628          | 13.5464 |
| 0.0001        | 70.18  | 7000  | 0.3804          | 13.4985 |
| 0.0001        | 80.2   | 8000  | 0.3961          | 13.5298 |
| 0.0           | 90.23  | 9000  | 0.4117          | 13.5650 |
| 0.0           | 100.25 | 10000 | 0.4282          | 13.6246 |
| 0.0001        | 110.28 | 11000 | 0.3542          | 13.0061 |
| 0.0001        | 120.3  | 12000 | 0.3697          | 13.1282 |
| 0.0           | 130.33 | 13000 | 0.3874          | 12.9934 |
| 0.0           | 140.35 | 14000 | 0.4002          | 12.9582 |
| 0.0           | 150.38 | 15000 | 0.4120          | 12.9455 |
| 0.0           | 160.4  | 16000 | 0.4246          | 12.9631 |
| 0.0           | 170.43 | 17000 | 0.4369          | 13.0071 |
| 0.0           | 180.45 | 18000 | 0.4501          | 13.0364 |
| 0.0           | 190.48 | 19000 | 0.4638          | 13.0374 |
| 0.0           | 200.5  | 20000 | 0.4786          | 13.0891 |
| 0.0001        | 210.53 | 21000 | 0.3785          | 12.7374 |
| 0.0           | 220.55 | 22000 | 0.4097          | 12.8166 |
| 0.0           | 230.58 | 23000 | 0.4236          | 12.8175 |
| 0.0           | 240.6  | 24000 | 0.4340          | 12.8039 |
| 0.0           | 250.63 | 25000 | 0.4431          | 12.8156 |
| 0.0           | 260.65 | 26000 | 0.4517          | 12.8058 |
| 0.0           | 270.68 | 27000 | 0.4601          | 12.7921 |
| 0.0           | 280.7  | 28000 | 0.4689          | 12.8029 |
| 0.0           | 290.73 | 29000 | 0.4774          | 12.8039 |
| 0.0           | 300.75 | 30000 | 0.4863          | 12.7960 |
| 0.0           | 310.78 | 31000 | 0.4949          | 12.7912 |
| 0.0           | 320.8  | 32000 | 0.5037          | 12.8107 |
| 0.0           | 330.83 | 33000 | 0.5115          | 12.8087 |
| 0.0           | 340.85 | 34000 | 0.5191          | 12.8293 |
| 0.0           | 350.88 | 35000 | 0.5256          | 12.8918 |
| 0.0           | 360.9  | 36000 | 0.5313          | 12.8810 |
| 0.0           | 370.93 | 37000 | 0.5361          | 12.9045 |
| 0.0           | 380.95 | 38000 | 0.5394          | 12.8996 |
| 0.0           | 390.98 | 39000 | 0.5417          | 12.9123 |
| 0.0           | 401.0  | 40000 | 0.5425          | 12.9123 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1