--- library_name: transformers license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-small-arabic-finetuned-on-halabi_daataset_with-diacritics-2 results: [] --- # whisper-small-arabic-finetuned-on-halabi_daataset_with-diacritics-2 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7378 - Wer: 0.7221 ## 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 | |:-------------:|:-------:|:----:|:---------------:|:------:| | 0.0504 | 3.5133 | 200 | 0.7435 | 0.7221 | | 0.0138 | 7.0177 | 400 | 0.9074 | 0.7135 | | 0.0049 | 10.5310 | 600 | 1.1826 | 0.7156 | | 0.0013 | 14.0354 | 800 | 1.1966 | 0.7156 | | 0.0008 | 17.5487 | 1000 | 1.1947 | 0.7163 | ### Framework versions - Transformers 4.47.0.dev0 - Pytorch 2.5.1 - Datasets 3.1.0 - Tokenizers 0.20.3