learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 32
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
num_epochs: 10

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.2197	1.0	265	0.3389	0.8837	0.8837	0.8837	0.8837
0.1799	2.0	530	0.3843	0.8866	0.8866	0.8866	0.8866
0.1528	3.0	795	0.4004	0.8913	0.8913	0.8913	0.8913
0.1284	4.0	1060	0.4922	0.8989	0.8989	0.8989	0.8989
0.1116	5.0	1325	0.4918	0.8960	0.8960	0.8960	0.8960
0.0964	6.0	1590	0.4743	0.8856	0.8856	0.8856	0.8856
0.0705	7.0	1855	0.5687	0.8984	0.8984	0.8984	0.8984
0.0654	8.0	2120	0.5976	0.8927	0.8927	0.8927	0.8927
0.0578	9.0	2385	0.6261	0.8932	0.8932	0.8932	0.8932
0.0463	10.0	2650	0.6291	0.8922	0.8922	0.8922	0.8922

salohnana2018/ABSA-SentencePair-DAPT-HARD-MDEBERTAV3-Run2

ABSA-SentencePair-DAPT-HARD-MDEBERTAV3-Run2