metadata
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-ft-cv-cy-en
results: []
whisper-large-v3-ft-cv-cy-en
This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4825
- Wer: 0.1979
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|---|---|---|---|---|
| 0.2506 | 2.0060 | 1000 | 0.3449 | 0.2113 |
| 0.0783 | 4.0120 | 2000 | 0.3657 | 0.2010 |
| 0.0377 | 6.0181 | 3000 | 0.4253 | 0.1986 |
| 0.0326 | 8.0241 | 4000 | 0.4601 | 0.1977 |
| 0.0313 | 10.0301 | 5000 | 0.4825 | 0.1979 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1