metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-with-augmentation-small-arabic_with-diacritics
results: []
whisper-with-augmentation-small-arabic_with-diacritics
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: 0.7564
- Wer: 0.7171
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 200
- training_steps: 1000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0489 | 3.5133 | 200 | 0.7624 | 0.7171 |
0.0143 | 7.0177 | 400 | 1.0633 | 0.7185 |
0.005 | 10.5310 | 600 | 1.0752 | 0.7178 |
0.0017 | 14.0354 | 800 | 1.1699 | 0.7127 |
0.0009 | 17.5487 | 1000 | 1.1766 | 0.7163 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3