learning_rate: 0.0001
train_batch_size: 1
eval_batch_size: 1
seed: 42
optimizer: Use 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	Accuracy	Precision	Recall	F1 score
1.1443	0.4205	2500	1.6635	0.6718	0.7829	0.4753	0.5915
1.0447	0.8410	5000	0.5585	0.7282	0.8149	0.5906	0.6849
0.9057	1.2616	7500	0.9051	0.7318	0.7275	0.7412	0.7343
0.8348	1.6821	10000	0.6307	0.7659	0.8742	0.6212	0.7263
0.7331	2.1026	12500	0.9500	0.7612	0.7489	0.7859	0.7669
0.6167	2.5231	15000	1.1524	0.7788	0.7970	0.7482	0.7718
0.6209	2.9437	17500	1.1690	0.7635	0.7872	0.7224	0.7534
0.4411	3.3642	20000	1.7563	0.7847	0.8438	0.6988	0.7645
0.4196	3.7847	22500	1.7767	0.7412	0.7204	0.7882	0.7528
0.292	4.2052	25000	2.0410	0.7624	0.7648	0.7576	0.7612
0.1791	4.6257	27500	2.1812	0.7706	0.7861	0.7435	0.7642

rishavranaut/flanT5_Task2

flanT5_Task2