--- library_name: transformers license: apache-2.0 base_model: openai/whisper-base tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-base-akan results: [] --- # whisper-base-akan This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1058 - Wer: 41.1088 ## 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: 32 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 1.8723 | 10.0 | 250 | 1.0427 | 68.4371 | | 0.3084 | 20.0 | 500 | 0.7759 | 44.8196 | | 0.0708 | 30.0 | 750 | 0.9140 | 42.7532 | | 0.027 | 40.0 | 1000 | 1.0043 | 42.5058 | | 0.0109 | 50.0 | 1250 | 1.0740 | 42.1711 | | 0.0046 | 60.0 | 1500 | 1.0846 | 40.9488 | | 0.0032 | 70.0 | 1750 | 1.1017 | 41.3708 | | 0.0022 | 80.0 | 2000 | 1.1058 | 41.1088 | ### Framework versions - Transformers 4.45.1 - Pytorch 2.4.1+cu121 - Datasets 3.0.1 - Tokenizers 0.20.0