metadata
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-small
metrics:
- wer
model-index:
- name: names-whisper-en-spectrogram-vanilla
results: []
names-whisper-en-spectrogram-vanilla
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: 0.0402
- Ner percent: 97.9270
- Wer: 1.0079
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 |
|---|---|---|---|---|---|
| 0.0037 | 5.0251 | 1000 | 0.0355 | 98.5904 | 0.9814 |
| 0.0006 | 10.0503 | 2000 | 0.0369 | 97.6783 | 0.9847 |
| 0.0003 | 15.0754 | 3000 | 0.0386 | 97.6783 | 0.9947 |
| 0.0002 | 20.1005 | 4000 | 0.0397 | 97.9270 | 1.0079 |
| 0.0002 | 25.1256 | 5000 | 0.0402 | 97.9270 | 1.0079 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1