---
language:
- gl
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 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: test
      args: gl
    metrics:
    - name: Wer
      type: wer
      value: 5.008278145695364
---

<!-- 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 Galician

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 gl dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2940
- Wer: 5.0083

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0176        | 5.0   | 1000  | 0.1563          | 5.2514 |
| 0.004         | 10.0  | 2000  | 0.1884          | 5.5653 |
| 0.0039        | 15.0  | 3000  | 0.2052          | 5.5377 |
| 0.0033        | 20.0  | 4000  | 0.2054          | 5.2997 |
| 0.0012        | 25.0  | 5000  | 0.2115          | 5.1031 |
| 0.001         | 30.0  | 6000  | 0.2195          | 5.2394 |
| 0.001         | 35.0  | 7000  | 0.2257          | 5.3446 |
| 0.001         | 40.0  | 8000  | 0.2178          | 5.4015 |
| 0.0008        | 45.0  | 9000  | 0.2250          | 5.4705 |
| 0.0008        | 50.0  | 10000 | 0.2320          | 5.2946 |
| 0.0002        | 55.0  | 11000 | 0.2368          | 5.3515 |
| 0.0           | 60.0  | 12000 | 0.2551          | 5.0997 |
| 0.0           | 65.0  | 13000 | 0.2634          | 5.0738 |
| 0.0           | 70.0  | 14000 | 0.2697          | 5.0359 |
| 0.0           | 75.0  | 15000 | 0.2752          | 5.0186 |
| 0.0           | 80.0  | 16000 | 0.2804          | 5.0066 |
| 0.0           | 85.0  | 17000 | 0.2852          | 4.9859 |
| 0.0           | 90.0  | 18000 | 0.2894          | 4.9893 |
| 0.0           | 95.0  | 19000 | 0.2927          | 5.0014 |
| 0.0           | 100.0 | 20000 | 0.2940          | 5.0083 |


### Framework versions

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