metadata
library_name: transformers
language:
- ps
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper small Ps - ZFA
results: []
Whisper small Ps - ZFA
This model is a fine-tuned version of openai/whisper-small on the Sir Shibli dataset. It achieves the following results on the evaluation set:
- Loss: 0.7353
- Wer: 26.1787
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 200
- training_steps: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 2.8341 | 300 | 0.5501 | 32.4650 |
| 5.4773 | 5.6635 | 600 | 0.5894 | 28.7836 |
| 5.4773 | 8.4929 | 900 | 0.6551 | 27.0398 |
| 0.1933 | 11.3223 | 1200 | 0.7140 | 26.7600 |
| 0.0125 | 14.1517 | 1500 | 0.7353 | 26.1787 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2