metadata
base_model: openai/whisper-large-v3
datasets:
- audiofolder
library_name: peft
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: whisper-v3-LoRA-en_students_test_2
results: []
whisper-v3-LoRA-en_students_test_2
This model is a fine-tuned version of openai/whisper-large-v3 on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3590
- Wer: 12.3268
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 100000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.9094 | 0.1270 | 500 | 0.6347 | 24.3686 |
| 0.5517 | 0.2541 | 1000 | 0.4835 | 18.0769 |
| 0.5364 | 0.3811 | 1500 | 0.4330 | 15.1149 |
| 0.5503 | 0.5081 | 2000 | 0.4113 | 13.6524 |
| 0.6521 | 0.6352 | 2500 | 0.3987 | 13.5897 |
| 0.6044 | 0.7622 | 3000 | 0.3912 | 13.0538 |
| 0.5487 | 0.8892 | 3500 | 0.3835 | 12.6119 |
| 0.5297 | 1.0163 | 4000 | 0.3791 | 12.4408 |
| 0.46 | 1.1433 | 4500 | 0.3751 | 12.3525 |
| 0.4947 | 1.2703 | 5000 | 0.3721 | 12.1415 |
| 0.524 | 1.3974 | 5500 | 0.3682 | 13.0139 |
| 0.4743 | 1.5244 | 6000 | 0.3649 | 13.3388 |
| 0.5338 | 1.6514 | 6500 | 0.3621 | 12.9397 |
| 0.5162 | 1.7785 | 7000 | 0.3597 | 13.3246 |
| 0.5004 | 1.9055 | 7500 | 0.3590 | 12.3268 |
Framework versions
- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1