---
language:
- gl
license: apache-2.0
base_model: openai/whisper-large
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large 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: 6.500536091031715
---

<!-- 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 Galician

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_13_0 gl dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3219
- Wer: 6.5005

## 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    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 0.0476        | 5.83   | 1000  | 0.1829          | 6.3535 |
| 0.008         | 11.66  | 2000  | 0.2224          | 6.2705 |
| 0.0043        | 17.49  | 3000  | 0.2360          | 6.3397 |
| 0.0029        | 23.32  | 4000  | 0.2544          | 6.5386 |
| 0.0036        | 29.15  | 5000  | 0.2552          | 6.6977 |
| 0.0026        | 34.99  | 6000  | 0.2737          | 6.8568 |
| 0.0009        | 40.82  | 7000  | 0.2734          | 6.6320 |
| 0.0009        | 46.65  | 8000  | 0.2769          | 6.8187 |
| 0.0006        | 52.48  | 9000  | 0.2832          | 6.6164 |
| 0.0013        | 58.31  | 10000 | 0.2883          | 7.0176 |
| 0.0005        | 64.14  | 11000 | 0.2972          | 6.8983 |
| 0.0006        | 69.97  | 12000 | 0.2964          | 6.6735 |
| 0.0003        | 75.8   | 13000 | 0.3042          | 6.7392 |
| 0.0002        | 81.63  | 14000 | 0.3084          | 6.7426 |
| 0.0001        | 87.46  | 15000 | 0.3145          | 6.6631 |
| 0.0002        | 93.29  | 16000 | 0.3091          | 6.6666 |
| 0.0001        | 99.13  | 17000 | 0.3170          | 6.8758 |
| 0.0002        | 104.96 | 18000 | 0.3223          | 6.6337 |
| 0.0           | 110.79 | 19000 | 0.3219          | 6.4971 |
| 0.0001        | 116.62 | 20000 | 0.3219          | 6.5005 |


### Framework versions

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