--- license: apache-2.0 base_model: ntu-spml/distilhubert tags: - generated_from_trainer datasets: - acordes_completo metrics: - accuracy model-index: - name: distilhubert-finetuned-chorddetection2 results: [] --- # distilhubert-finetuned-chorddetection2 This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co./ntu-spml/distilhubert) on the ChordStimation2 dataset. It achieves the following results on the evaluation set: - Loss: 0.0000 - Accuracy: 1.0 ## 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: 5e-05 - train_batch_size: 8 - 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_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.4498 | 1.0 | 3025 | 0.4276 | 0.9367 | | 0.0007 | 2.0 | 6050 | 0.0389 | 0.9899 | | 0.119 | 3.0 | 9075 | 0.0704 | 0.9863 | | 0.0 | 4.0 | 12100 | 0.0000 | 1.0 | | 0.0 | 5.0 | 15125 | 0.0000 | 1.0 | | 0.0 | 6.0 | 18150 | 0.0004 | 1.0 | | 0.0 | 7.0 | 21175 | 0.0009 | 0.9998 | | 0.0 | 8.0 | 24200 | 0.0000 | 1.0 | | 0.0 | 9.0 | 27225 | 0.0000 | 1.0 | | 0.0 | 10.0 | 30250 | 0.0000 | 1.0 | ### Framework versions - Transformers 4.35.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1