metadata
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- atlasia/darija_bible_aligned
metrics:
- wer
model-index:
- name: whisper-tiny-darija-finetune-Anas
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: darija_bible_aligned
type: atlasia/darija_bible_aligned
metrics:
- name: Wer
type: wer
value: 21.451929365598428
whisper-tiny-darija-finetune-Anas
This model is a fine-tuned version of openai/whisper-tiny on the darija_bible_aligned dataset. It achieves the following results on the evaluation set:
- Loss: 0.1978
- Wer: 21.4519
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 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_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.202 | 1.0 | 888 | 0.1978 | 21.4519 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1