metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-ft-btb-ca-ec-cv-cy-en
results: []
whisper-base-ft-btb-ca-ec-cv-cy-en
This model is a fine-tuned version of openai/whisper-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7135
- Wer: 0.5089
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 |
|---|---|---|---|---|
| 1.7363 | 0.3260 | 1000 | 0.9845 | 0.6733 |
| 1.4155 | 0.6520 | 2000 | 0.8237 | 0.5717 |
| 1.3809 | 0.9780 | 3000 | 0.7566 | 0.5274 |
| 1.0882 | 1.3040 | 4000 | 0.7265 | 0.5286 |
| 1.0903 | 1.6300 | 5000 | 0.7135 | 0.5089 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.1