metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-ft-btb-ca-cy
results: []
whisper-large-v3-ft-btb-ca-cy
This model is a fine-tuned version of openai/whisper-large-v3 on the DewiBrynJones/banc-trawsgrifiadau-bangor-clean train main, cymen-arfor/25awr train+dev main dataset. It achieves the following results on the evaluation set:
- Loss: 0.3810
- Wer: 0.2750
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 |
|---|---|---|---|---|
| 0.5152 | 0.5411 | 1000 | 0.4954 | 0.3535 |
| 0.3339 | 1.0823 | 2000 | 0.4205 | 0.3198 |
| 0.3189 | 1.6234 | 3000 | 0.3911 | 0.2913 |
| 0.2051 | 2.1645 | 4000 | 0.3863 | 0.2790 |
| 0.202 | 2.7056 | 5000 | 0.3810 | 0.2750 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3