learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 23
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

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.1831	1.0	265	0.3572	0.8842	0.8842	0.8842	0.8842
0.1553	2.0	530	0.4496	0.8946	0.8946	0.8946	0.8946
0.1295	3.0	795	0.5031	0.8663	0.8663	0.8663	0.8663
0.1087	4.0	1060	0.4758	0.8908	0.8908	0.8908	0.8908
0.102	5.0	1325	0.5084	0.8889	0.8889	0.8889	0.8889
0.0757	6.0	1590	0.5843	0.8861	0.8861	0.8861	0.8861
0.071	7.0	1855	0.5743	0.8960	0.8960	0.8960	0.8960
0.0542	8.0	2120	0.6425	0.8951	0.8951	0.8951	0.8951
0.0484	9.0	2385	0.6409	0.8946	0.8946	0.8946	0.8946
0.0421	10.0	2650	0.6512	0.8927	0.8927	0.8927	0.8927

salohnana2018/ABSA-SentencePair-DAPT-HARD-MDEBERTAV3-Run3

ABSA-SentencePair-DAPT-HARD-MDEBERTAV3-Run3