learning_rate: 1.510606094120106e-05
train_batch_size: 32
eval_batch_size: 32
seed: 2024
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training Loss	Epoch	Step	Validation Loss	Hamming Loss	Zero One Loss	Jaccard Score	Hamming Loss Optimised	Hamming Loss Threshold	Zero One Loss Optimised	Zero One Loss Threshold	Jaccard Score Optimised	Jaccard Score Threshold
No log	1.0	100	0.7202	0.4325	1.0	0.8586	0.1123	0.7924	0.8712	0.7112	0.8203	0.5766
No log	2.0	200	0.6922	0.3761	1.0	0.8520	0.1123	0.7829	0.8812	0.6982	0.8546	0.5904
No log	3.0	300	0.6696	0.349	1.0	0.8606	0.1123	0.7641	0.885	0.6857	0.8436	0.6634
No log	4.0	400	0.6555	0.3432	1.0	0.8662	0.1121	0.7518	0.8825	0.6757	0.8455	0.6604
0.6931	5.0	500	0.6509	0.3414	1.0	0.8678	0.1121	0.7504	0.8812	0.6730	0.8449	0.6539

ElMad/grandiose-horse-172

grandiose-horse-172