learning_rate: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training Loss	Epoch	Step	Validation Loss	Accuracy	Auc	F1	Precision	Recall
1.7739	1.0	311	0.8898	0.623	0.683	0.58	0.523	0.653
0.726	2.0	622	0.6793	0.701	0.77	0.673	0.597	0.771
0.5642	3.0	933	0.6046	0.72	0.791	0.68	0.626	0.746
0.5018	4.0	1244	0.5779	0.728	0.804	0.685	0.637	0.74
0.4623	5.0	1555	0.5831	0.721	0.811	0.691	0.62	0.78
0.4352	6.0	1866	0.5661	0.735	0.815	0.694	0.643	0.754
0.415	7.0	2177	0.5631	0.739	0.818	0.696	0.651	0.749
0.3993	8.0	2488	0.5638	0.742	0.818	0.7	0.653	0.754
0.3891	9.0	2799	0.5646	0.739	0.819	0.697	0.65	0.751
0.3809	10.0	3110	0.5642	0.737	0.819	0.694	0.649	0.746

MoNafea01/saudi-eou-qwen-classifier

saudi-eou-qwen-classifier