--- license: bsd-3-clause base_model: MIT/ast-finetuned-audioset-10-10-0.4593 tags: - generated_from_trainer metrics: - accuracy model-index: - name: S5_M1_f3_AST_42783290 results: [] --- # S5_M1_f3_AST_42783290 This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0127 - Accuracy: 0.9984 ## 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: 3e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.0059 | 1.0 | 368 | 0.0092 | 0.9976 | | 0.0001 | 2.0 | 737 | 0.0139 | 0.9984 | | 0.0072 | 3.0 | 1105 | 0.0037 | 0.9984 | | 0.0 | 4.0 | 1474 | 0.0135 | 0.9984 | | 0.0 | 4.99 | 1840 | 0.0127 | 0.9984 | ### Framework versions - Transformers 4.32.1 - Pytorch 2.1.2 - Datasets 2.16.1 - Tokenizers 0.13.3