metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: no-voice-clone-large-finetune-test
results: []
no-voice-clone-large-finetune-test
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: 0.4622
- Wer: 20.1897
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0088 | 4.6729 | 250 | 0.5014 | 21.1681 |
| 0.0079 | 9.3458 | 500 | 0.5158 | 29.2321 |
| 0.0001 | 14.0187 | 750 | 0.4311 | 23.9253 |
| 0.0 | 18.6916 | 1000 | 0.4457 | 20.5752 |
| 0.0 | 23.3645 | 1250 | 0.4520 | 20.6048 |
| 0.0 | 28.0374 | 1500 | 0.4560 | 20.1897 |
| 0.0 | 32.7103 | 1750 | 0.4588 | 20.1601 |
| 0.0 | 37.3832 | 2000 | 0.4607 | 20.1304 |
| 0.0 | 42.0561 | 2250 | 0.4618 | 20.2490 |
| 0.0 | 46.7290 | 2500 | 0.4622 | 20.1897 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3