---
language:
- gl
license: apache-2.0
base_model: openai/whisper-medium
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Medium Galician
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_13_0 gl
      type: mozilla-foundation/common_voice_13_0
      config: gl
      split: validation
      args: gl
    metrics:
    - name: Wer
      type: wer
      value: 6.433092380590046
---

<!-- 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 Galician

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_13_0 gl dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2829
- Wer: 6.4331

## 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
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0825        | 5.81  | 1000  | 0.1863          | 7.0141 |
| 0.0138        | 11.63 | 2000  | 0.2197          | 6.6873 |
| 0.0059        | 17.44 | 3000  | 0.2436          | 6.5922 |
| 0.0033        | 23.26 | 4000  | 0.2536          | 6.5040 |
| 0.002         | 29.07 | 5000  | 0.2606          | 6.6925 |
| 0.002         | 34.88 | 6000  | 0.2690          | 6.6890 |
| 0.001         | 40.7  | 7000  | 0.2734          | 6.5853 |
| 0.0007        | 46.51 | 8000  | 0.2821          | 6.4798 |
| 0.0006        | 52.33 | 9000  | 0.2829          | 6.4331 |
| 0.0007        | 58.14 | 10000 | 0.2847          | 6.4452 |


### Framework versions

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