SeizureClassifier_AST_B_43829950

This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0063
• 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: 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: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.269	0.99	44	1.1676	0.8564
0.7525	1.99	88	0.5446	0.9777
0.3005	2.98	132	0.2273	0.9876
0.185	4.0	177	0.1556	0.9653
0.0935	4.99	221	0.0798	0.9901
0.0545	5.99	265	0.0313	0.9950
0.0416	6.98	309	0.0278	0.9950
0.0264	8.0	354	0.0682	0.9851
0.0109	8.99	398	0.0311	0.9950
0.0104	9.99	442	0.0085	1.0
0.0083	10.98	486	0.0143	0.9975
0.0067	12.0	531	0.0070	1.0
0.0063	12.99	575	0.0066	1.0
0.006	13.99	619	0.0064	1.0
0.0059	14.92	660	0.0063	1.0

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.2+cu118
• Datasets 2.16.1
• Tokenizers 0.15.0