learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
distributed_type: not_parallel
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: 20

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.7452	1.0	250	0.2530	0.917	0.9181	0.9220	0.917
0.1966	2.0	500	0.1587	0.933	0.9328	0.9335	0.933
0.1318	3.0	750	0.1462	0.9415	0.9421	0.9444	0.9415
0.1003	4.0	1000	0.1566	0.939	0.9397	0.9421	0.939
0.0827	5.0	1250	0.1522	0.9375	0.9377	0.9393	0.9375
0.0687	6.0	1500	0.1601	0.9415	0.9416	0.9421	0.9415
0.0545	7.0	1750	0.1773	0.9385	0.9380	0.9379	0.9385
0.0450	8.0	2000	0.1943	0.941	0.9411	0.9415	0.941
0.0368	9.0	2250	0.2081	0.9415	0.9416	0.9422	0.9415
0.0282	10.0	2500	0.2551	0.936	0.9359	0.9374	0.936
0.0221	11.0	2750	0.2443	0.9335	0.9335	0.9336	0.9335
0.0225	12.0	3000	0.2585	0.94	0.9401	0.9407	0.94
0.0184	13.0	3250	0.2594	0.939	0.9387	0.9386	0.939
0.0124	14.0	3500	0.2676	0.937	0.9371	0.9374	0.937
0.0122	15.0	3750	0.2866	0.9375	0.9375	0.9375	0.9375
0.0126	16.0	4000	0.2912	0.937	0.9368	0.9368	0.937
0.0116	17.0	4250	0.2915	0.941	0.9407	0.9406	0.941
0.0101	18.0	4500	0.2943	0.938	0.9380	0.9381	0.938
0.0100	19.0	4750	0.2952	0.9425	0.9423	0.9424	0.9425
0.0065	20.0	5000	0.2946	0.9415	0.9413	0.9413	0.9415

long290604/distilbert-base-uncased-finetuned-emotion

distilbert-base-uncased-finetuned-emotion