README.md

---
library_name: transformers
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-ft-cv-cy-en
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-large-v3-turbo-ft-cv-cy-en

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the DewiBrynJones/commonvoice_18_0_cy_en train main dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2927
- Wer: 0.1577

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.6485        | 0.7075 | 1000 | 0.3581          | 0.2210 |
| 0.3362        | 1.4149 | 2000 | 0.3094          | 0.1831 |
| 0.1504        | 2.1224 | 3000 | 0.2957          | 0.1699 |
| 0.1558        | 2.8299 | 4000 | 0.2816          | 0.1646 |
| 0.0619        | 3.5373 | 5000 | 0.2927          | 0.1577 |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.0.2
- Tokenizers 0.20.1