metadata
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-ft-cy
results: []
language:
- cy
- en
pipeline_tag: automatic-speech-recognition
whisper-large-v3-ft-cy-en
This model is a fine-tuned version of openai/whisper-large-v3 on Welsh and English bilingual data originally from Mozilla's Common Voice dataset (see: techiaith/commonvoice_16_1_en_cy).
It achieves the following results on the evaluation set:
- Loss: 0.1480
- Wer: 25.1341
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: 4
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|
| 0.2078 | 0.25 | 1000 | 0.2198 | 28.7556 |
| 0.1623 | 0.5 | 2000 | 0.1800 | 31.3698 |
| 0.1417 | 0.75 | 3000 | 0.1585 | 18.7051 |
| 0.1188 | 1.01 | 4000 | 0.1480 | 25.1341 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1