metadata
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-small
metrics:
- wer
model-index:
- name: names-whisper-en-spectrogram-new-method
results: []
names-whisper-en-spectrogram-new-method
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0374
- Ner percent: 98.7838
- Wer: 0.8407
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: 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 | Ner percent | Wer |
|---|---|---|---|---|---|
| 0.0039 | 5.0505 | 1000 | 0.0352 | 97.8378 | 1.1843 |
| 0.0005 | 10.1010 | 2000 | 0.0350 | 98.9189 | 0.8674 |
| 0.0003 | 15.1515 | 3000 | 0.0361 | 98.7838 | 0.8340 |
| 0.0002 | 20.2020 | 4000 | 0.0370 | 98.7838 | 0.8373 |
| 0.0002 | 25.2525 | 5000 | 0.0374 | 98.7838 | 0.8407 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1