learning_rate: 0.001
train_batch_size: 16
eval_batch_size: 16
seed: 42
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: 150
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	F1 Micro	F1 Macro	Accuracy	Rate
No log	1.0	1	3.1514	0.0	0.0	0.0	0.001
No log	2.0	2	3.1508	0.0	0.0	0.0	0.001
No log	3.0	3	3.1557	0.0	0.0	0.0	0.001
No log	4.0	4	3.1625	0.0	0.0	0.0	0.001
No log	5.0	5	3.1223	0.2	0.0571	0.2	0.001
No log	6.0	6	3.1340	0.1	0.04	0.1	0.001
No log	7.0	7	3.1654	0.2	0.0606	0.2	0.001
No log	8.0	8	3.1547	0.3	0.1667	0.3	0.001
No log	9.0	9	3.1387	0.3	0.1667	0.3	0.001
No log	10.0	10	3.1150	0.3	0.1481	0.3	0.001
No log	11.0	11	3.0898	0.3	0.1667	0.3	0.001
No log	12.0	12	3.0465	0.1	0.0444	0.1	0.001
No log	13.0	13	3.0262	0.1	0.05	0.1	0.001
No log	14.0	14	3.0098	0.2	0.1222	0.2	0.001
No log	15.0	15	3.0078	0.2	0.1371	0.2	0.001
No log	16.0	16	3.0350	0.2	0.1371	0.2	0.001
No log	17.0	17	3.0396	0.2	0.1467	0.2	0.001
No log	18.0	18	3.0520	0.1	0.0667	0.1	0.001
No log	19.0	19	3.0697	0.1	0.0667	0.1	0.001
No log	20.0	20	3.1036	0.2	0.1467	0.2	0.001
No log	21.0	21	3.1122	0.2	0.16	0.2	0.001
No log	22.0	22	3.1102	0.1	0.08	0.1	0.0001
No log	23.0	23	3.1098	0.2	0.16	0.2	0.0001
No log	24.0	24	3.1053	0.2	0.1467	0.2	0.0001
No log	25.0	25	3.0939	0.2	0.16	0.2	0.0001

Amoros/DinoAmoros-small-2025_05_06_35666-prova_bs16_freeze_monolabel

DinoAmoros-small-2025_05_06_35666-prova_bs16_freeze_monolabel