metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mina
results: []
mina
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: 0.3404
- Wer: 0.2722
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 50
- training_steps: 12000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7658 | 0.3040 | 500 | 0.4899 | 3.0318 |
| 0.4325 | 0.6079 | 1000 | 0.4118 | 1.6752 |
| 0.379 | 0.9119 | 1500 | 0.3764 | 2.0571 |
| 0.2677 | 1.2158 | 2000 | 0.3626 | 1.5884 |
| 0.2349 | 1.5198 | 2500 | 0.3496 | 0.3929 |
| 0.2304 | 1.8237 | 3000 | 0.3383 | 0.4325 |
| 0.1852 | 2.1277 | 3500 | 0.3402 | 0.2619 |
| 0.1351 | 2.4316 | 4000 | 0.3372 | 0.4407 |
| 0.1352 | 2.7356 | 4500 | 0.3346 | 0.2663 |
| 0.126 | 3.0395 | 5000 | 0.3404 | 0.2722 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0+cu121
- Datasets 3.6.0
- Tokenizers 0.20.3