--- library_name: transformers license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-small-akan results: [] --- # whisper-small-akan 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: 0.9537 - Wer: 35.7102 ## 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: 0.0001 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 2000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0761 | 10.0 | 250 | 0.6787 | 41.9921 | | 0.0557 | 20.0 | 500 | 0.7485 | 42.4731 | | 0.0273 | 30.0 | 750 | 0.8616 | 40.3509 | | 0.0123 | 40.0 | 1000 | 0.9085 | 38.3701 | | 0.0024 | 50.0 | 1250 | 0.9378 | 36.7572 | | 0.0002 | 60.0 | 1500 | 0.9400 | 36.5025 | | 0.0001 | 70.0 | 1750 | 0.9507 | 35.9366 | | 0.0001 | 80.0 | 2000 | 0.9537 | 35.7102 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1