---
language:
- gl
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large-V2 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: 5.701587521184242
---

<!-- 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-V2 Galician

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_13_0 gl dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2981
- Wer: 5.7016

## 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    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 0.0659        | 5.83   | 1000  | 0.1663          | 5.9593 |
| 0.0164        | 11.66  | 2000  | 0.1947          | 5.5044 |
| 0.0069        | 17.49  | 3000  | 0.2165          | 5.7500 |
| 0.0052        | 23.32  | 4000  | 0.2292          | 5.9212 |
| 0.0032        | 29.15  | 5000  | 0.2320          | 5.8884 |
| 0.0037        | 34.99  | 6000  | 0.2434          | 6.0647 |
| 0.0022        | 40.82  | 7000  | 0.2465          | 6.1114 |
| 0.0019        | 46.65  | 8000  | 0.2531          | 5.8590 |
| 0.0009        | 52.48  | 9000  | 0.2567          | 5.8451 |
| 0.001         | 58.31  | 10000 | 0.2718          | 5.7673 |
| 0.0011        | 64.14  | 11000 | 0.2659          | 6.1045 |
| 0.0008        | 69.97  | 12000 | 0.2765          | 6.0405 |
| 0.0006        | 75.8   | 13000 | 0.2793          | 6.0250 |
| 0.0004        | 81.63  | 14000 | 0.2848          | 6.0025 |
| 0.0005        | 87.46  | 15000 | 0.2790          | 5.9454 |
| 0.0002        | 93.29  | 16000 | 0.2884          | 5.8175 |
| 0.0002        | 99.13  | 17000 | 0.2913          | 5.7898 |
| 0.0001        | 104.96 | 18000 | 0.2901          | 5.7258 |
| 0.0001        | 110.79 | 19000 | 0.2991          | 5.7050 |
| 0.0001        | 116.62 | 20000 | 0.2981          | 5.7016 |


### Framework versions

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