learning_rate: 2e-05
train_batch_size: 128
eval_batch_size: 128
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: 16

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
1.0338	1.0	125	0.4268	0.8755	0.8667
0.2848	2.0	250	0.2057	0.928	0.9285
0.1571	3.0	375	0.1687	0.9355	0.9360
0.1195	4.0	500	0.1462	0.935	0.9356
0.0995	5.0	625	0.1474	0.9345	0.9346
0.0829	6.0	750	0.1498	0.936	0.9362
0.0758	7.0	875	0.1517	0.9335	0.9333
0.0649	8.0	1000	0.1571	0.935	0.9351
0.0536	9.0	1125	0.1622	0.9385	0.9383
0.0453	10.0	1250	0.1678	0.937	0.9370
0.0400	11.0	1375	0.1752	0.938	0.9380
0.0354	12.0	1500	0.1839	0.938	0.9379
0.0295	13.0	1625	0.1868	0.938	0.9378
0.0279	14.0	1750	0.1912	0.9365	0.9369
0.0271	15.0	1875	0.1942	0.9385	0.9383
0.0212	16.0	2000	0.1922	0.9365	0.9364

steve202608/distilbert-base-uncased-finetuned-emotion

distilbert-base-uncased-finetuned-emotion