metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: finetune-whisper-base.en
results: []
finetune-whisper-base.en
This model is a fine-tuned version of openai/whisper-base.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3797
- Wer Ortho: 12.8163
- Wer: 9.1352
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: 16
- 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: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.7801 | 0.8065 | 100 | 0.3812 | 13.3555 | 9.4194 |
| 0.2817 | 1.6129 | 200 | 0.3647 | 12.5674 | 9.1352 |
| 0.1853 | 2.4194 | 300 | 0.3705 | 12.7748 | 8.8510 |
| 0.146 | 3.2258 | 400 | 0.3738 | 12.5674 | 9.0946 |
| 0.1097 | 4.0323 | 500 | 0.3797 | 12.8163 | 9.1352 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1