learning_rate: 5e-06
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.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: 20

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.6272	1.0	196	0.6521	0.7033	0.6949	0.6949	0.7033
0.5687	2.0	392	0.6339	0.7233	0.7150	0.7302	0.7233
0.4809	3.0	588	0.6047	0.7567	0.7527	0.7541	0.7567
0.3967	4.0	784	0.6087	0.7567	0.7514	0.7571	0.7567
0.3732	5.0	980	0.6366	0.7633	0.7589	0.7571	0.7633
0.2892	6.0	1176	0.7116	0.7533	0.7472	0.7481	0.7533
0.3633	7.0	1372	0.7308	0.7533	0.7456	0.7440	0.7533
0.2847	8.0	1568	0.7624	0.75	0.7422	0.7473	0.75
0.2652	9.0	1764	0.8204	0.7433	0.7372	0.7367	0.7433
0.22	10.0	1960	0.8618	0.7333	0.7250	0.7231	0.7333
0.1766	11.0	2156	0.8491	0.7367	0.7314	0.7311	0.7367
0.1237	12.0	2352	0.9106	0.7533	0.7489	0.7480	0.7533
0.1694	13.0	2548	0.9444	0.7467	0.7443	0.7426	0.7467
0.149	14.0	2744	1.0079	0.7367	0.7307	0.7284	0.7367
0.1163	15.0	2940	1.0527	0.7433	0.7382	0.7360	0.7433
0.1153	16.0	3136	1.0669	0.7433	0.7394	0.7374	0.7433
0.0927	17.0	3332	1.1076	0.74	0.7351	0.7341	0.74
0.0548	18.0	3528	1.1197	0.7467	0.7419	0.7398	0.7467
0.1229	19.0	3724	1.1201	0.7433	0.7385	0.7363	0.7433
0.0661	20.0	3920	1.1324	0.7433	0.7385	0.7363	0.7433

ClemensK/cultural-bert-base-cased-classifier

cultural-bert-base-cased-classifier