---
language:
- eu
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large-V3 Basque
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_13_0 eu
      type: mozilla-foundation/common_voice_13_0
      config: eu
      split: test
      args: eu
    metrics:
    - name: Wer
      type: wer
      value: 10.620114220908098
---

<!-- 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 Large-V3 Basque

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the mozilla-foundation/common_voice_13_0 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3803
- Wer: 10.6201

## 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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0326        | 4.85  | 1000  | 0.2300          | 13.3278 |
| 0.004         | 9.71  | 2000  | 0.2723          | 12.2038 |
| 0.0058        | 14.56 | 3000  | 0.2771          | 12.4246 |
| 0.003         | 19.42 | 4000  | 0.2838          | 12.2119 |
| 0.003         | 24.27 | 5000  | 0.2740          | 11.7704 |
| 0.0014        | 29.13 | 6000  | 0.2936          | 11.5436 |
| 0.0015        | 33.98 | 7000  | 0.2911          | 11.5193 |
| 0.0012        | 38.83 | 8000  | 0.2939          | 11.3674 |
| 0.0009        | 43.69 | 9000  | 0.3039          | 11.4140 |
| 0.0002        | 48.54 | 10000 | 0.3063          | 10.9624 |
| 0.0009        | 53.4  | 11000 | 0.3014          | 11.3350 |
| 0.0011        | 58.25 | 12000 | 0.3052          | 11.0474 |
| 0.0001        | 63.11 | 13000 | 0.3204          | 10.8692 |
| 0.0           | 67.96 | 14000 | 0.3413          | 10.7092 |
| 0.0           | 72.82 | 15000 | 0.3524          | 10.6647 |
| 0.0           | 77.67 | 16000 | 0.3607          | 10.6566 |
| 0.0           | 82.52 | 17000 | 0.3675          | 10.6120 |
| 0.0           | 87.38 | 18000 | 0.3737          | 10.6140 |
| 0.0           | 92.23 | 19000 | 0.3782          | 10.6181 |
| 0.0           | 97.09 | 20000 | 0.3803          | 10.6201 |


### Framework versions

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