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---
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 |