--- library_name: transformers language: - wi license: apache-2.0 base_model: openai/whisper-tiny tags: - custom-dataset - local-dataset - whisper - generated_from_trainer metrics: - wer model-index: - name: Whisper-FineTuned-DL-Twi results: [] --- # Whisper-FineTuned-DL-Twi This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Twi- native Ghanaian language. dataset. It achieves the following results on the evaluation set: - Loss: 0.0063 - Wer: 17.9909 - Cer: 17.8277 ## 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 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: 500 - training_steps: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:------:|:----:|:---------------:|:-------:|:-------:| | 0.0201 | 0.6333 | 1000 | 0.0259 | 40.8149 | 33.1641 | | 0.006 | 1.2666 | 2000 | 0.0104 | 21.3751 | 15.7877 | | 0.009 | 1.8999 | 3000 | 0.0070 | 17.9131 | 16.0698 | | 0.0034 | 2.5332 | 4000 | 0.0063 | 17.9909 | 17.8277 | ### Framework versions - Transformers 4.48.0.dev0 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0