---
library_name: transformers
language:
- eu
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Large Basque
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_17_0 eu
      type: mozilla-foundation/common_voice_17_0
      config: eu
      split: test
      args: eu
    metrics:
    - name: Wer
      type: wer
      value: 7.215361500971087
---

<!-- 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 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_17_0 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1259
- Wer: 7.2154

## 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: 4.375e-06
- train_batch_size: 16
- eval_batch_size: 8
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2208        | 0.05   | 500  | 0.2592          | 20.6915 |
| 0.1489        | 0.1    | 1000 | 0.1971          | 14.6827 |
| 0.1973        | 0.15   | 1500 | 0.1747          | 12.3777 |
| 0.1353        | 1.0296 | 2000 | 0.1527          | 10.7195 |
| 0.1065        | 1.0796 | 2500 | 0.1456          | 9.8694  |
| 0.106         | 1.1296 | 3000 | 0.1362          | 9.0925  |
| 0.0718        | 2.0092 | 3500 | 0.1326          | 8.5428  |
| 0.0683        | 2.0592 | 4000 | 0.1343          | 8.4851  |
| 0.0482        | 2.1092 | 4500 | 0.1336          | 8.1049  |
| 0.0548        | 2.1592 | 5000 | 0.1316          | 7.9244  |
| 0.0282        | 3.0388 | 5500 | 0.1391          | 7.8182  |
| 0.025         | 3.0888 | 6000 | 0.1425          | 7.9409  |
| 0.0274        | 3.1388 | 6500 | 0.1391          | 7.7311  |
| 0.0155        | 4.0184 | 7000 | 0.1492          | 7.6972  |
| 0.0189        | 4.0684 | 7500 | 0.1517          | 7.6569  |
| 0.0139        | 4.1184 | 8000 | 0.1539          | 7.6267  |
| 0.0141        | 4.1684 | 8500 | 0.1550          | 7.5424  |
| 0.0368        | 5.048  | 9000 | 0.1259          | 7.2154  |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.2.dev0
- Tokenizers 0.20.0