---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
language:
- cy
- en
pipeline_tag: automatic-speech-recognition
datasets:
- techiaith/commonvoice_18_0_cy_en
---

# whisper-large-v3-ft-cy-en

This model is a version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) fine-tuned with a curated collection of
Welsh and English speech data (see: [techiaith/commonvoice_18_0_cy_en](https://huggingface.co/datasets/techiaith/commonvoice_18_0_cy_en) 
collected originally from Mozilla's Common Voice project.

It achieves the following results on the following language specific test sets:

- WER (test_en): 13.85
- WER (test_cy): 8.78
- WER (test_cy+test_en): 9.55

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2097        | 0.2497 | 1000 | 0.2169          | 14.2221 |
| 0.1621        | 0.4993 | 2000 | 0.1816          | 11.6845 |
| 0.1406        | 0.7490 | 3000 | 0.1609          | 10.2445 |
| 0.1242        | 0.9987 | 4000 | 0.1505          | 9.5594  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1