learning_rate: 1e-05
train_batch_size: 50
eval_batch_size: 50
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 200
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
num_epochs: 10
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	57	0.6660	0.7275	0.7839	0.6286	0.6977
No log	2.0	114	0.4785	0.7684	0.7575	0.7898	0.7733
No log	3.0	171	0.4713	0.7861	0.7676	0.8210	0.7934
No log	4.0	228	0.4672	0.7872	0.7625	0.8345	0.7969
No log	5.0	285	0.4651	0.7829	0.7586	0.8303	0.7928
No log	6.0	342	0.4509	0.7890	0.7724	0.8196	0.7953
No log	7.0	399	0.4486	0.7918	0.7811	0.8111	0.7958
No log	8.0	456	0.4441	0.8	0.7760	0.8438	0.8084
1.9510	9.0	513	0.4432	0.8004	0.7776	0.8416	0.8083
1.9510	10.0	570	0.4428	0.8004	0.7835	0.8303	0.8062

sms112/euk_roberta_base_essentiality_Network

euk_roberta_base_essentiality_Network