metadata
library_name: peft
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
model-index:
- name: whisper-turbo-tr_All_datasets_finetune
results: []
whisper-turbo-tr_All_datasets_finetune
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1497
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: 8
- seed: 42
- 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_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1651 | 0.4869 | 1500 | 0.1745 |
| 0.158 | 0.9737 | 3000 | 0.1590 |
| 0.1391 | 1.4606 | 4500 | 0.1540 |
| 0.1509 | 1.9474 | 6000 | 0.1516 |
| 0.1387 | 2.4343 | 7500 | 0.1500 |
| 0.1428 | 2.9211 | 9000 | 0.1497 |
Framework versions
- PEFT 0.15.1
- Transformers 4.48.0
- Pytorch 2.5.1
- Datasets 3.0.0
- Tokenizers 0.21.1