metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: 2026-02-25_02-15-51
results: []
2026-02-25_02-15-51
This model is a fine-tuned version of openai/whisper-small.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2900
- Wer: 11.7695
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.1276 | 0.1123 | 500 | 0.3356 | 13.7752 |
| 0.2792 | 0.2247 | 1000 | 0.3113 | 12.9679 |
| 0.2666 | 0.3370 | 1500 | 0.3035 | 12.6108 |
| 0.2616 | 0.4493 | 2000 | 0.2999 | 12.2032 |
| 0.2563 | 0.5617 | 2500 | 0.2986 | 13.2479 |
| 0.2501 | 0.6740 | 3000 | 0.2929 | 12.4547 |
| 0.2561 | 0.7863 | 3500 | 0.2910 | 11.9032 |
| 0.2497 | 0.8987 | 4000 | 0.2898 | 12.0265 |
| 0.2336 | 1.0110 | 4500 | 0.2877 | 11.4051 |
| 0.1795 | 1.1233 | 5000 | 0.2915 | 11.8667 |
| 0.1837 | 1.2357 | 5500 | 0.2909 | 11.7313 |
| 0.1763 | 1.3480 | 6000 | 0.2900 | 11.7695 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1