learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
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: 30

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall	Precision	F1
No log	1.0	231	0.2719	0.9072	0.9263	0.9163	0.9212
No log	2.0	462	0.3650	0.9067	0.9452	0.9004	0.9223
0.1526	3.0	693	0.4611	0.9137	0.9462	0.9100	0.9277
0.1526	4.0	924	0.4861	0.9271	0.9412	0.9347	0.9380
0.025	5.0	1155	0.5708	0.9154	0.9432	0.9150	0.9289
0.025	6.0	1386	0.6532	0.9090	0.9512	0.8992	0.9245
0.0064	7.0	1617	0.6813	0.9084	0.9482	0.9007	0.9238
0.0064	8.0	1848	0.6611	0.9131	0.9532	0.9037	0.9278
0.0043	9.0	2079	0.5888	0.9224	0.9313	0.9359	0.9336
0.0043	10.0	2310	0.9218	0.8804	0.9641	0.8514	0.9043
0.0049	11.0	2541	0.6622	0.9078	0.9432	0.9036	0.9230
0.0049	12.0	2772	0.6939	0.9172	0.9462	0.9152	0.9305
0.003	13.0	3003	0.7052	0.9096	0.9532	0.8986	0.9251
0.003	14.0	3234	0.9217	0.8926	0.9661	0.8661	0.9134
0.003	15.0	3465	0.7322	0.9055	0.9402	0.9025	0.9210
0.0049	16.0	3696	0.6537	0.9183	0.9283	0.932	0.9301
0.0049	17.0	3927	0.7311	0.9119	0.9472	0.9066	0.9264
0.0031	18.0	4158	0.7479	0.9125	0.9452	0.9090	0.9268
0.0031	19.0	4389	0.7028	0.9137	0.9412	0.9139	0.9274
0.0013	20.0	4620	0.7262	0.9096	0.9412	0.9078	0.9242
0.0013	21.0	4851	0.6785	0.9125	0.9273	0.9236	0.9254
0.0015	22.0	5082	0.7053	0.9148	0.9333	0.9222	0.9277
0.0015	23.0	5313	0.6688	0.9207	0.9193	0.9438	0.9314
0.0013	24.0	5544	0.7291	0.9125	0.9363	0.9162	0.9261
0.0013	25.0	5775	0.7323	0.9107	0.9363	0.9135	0.9247
0.0016	26.0	6006	0.7450	0.9096	0.9373	0.9109	0.9239
0.0016	27.0	6237	0.7436	0.9102	0.9363	0.9126	0.9243
0.0016	28.0	6468	0.7080	0.9218	0.9313	0.935	0.9331
0.001	29.0	6699	0.7077	0.9218	0.9313	0.935	0.9331
0.001	30.0	6930	0.7020	0.9218	0.9313	0.935	0.9331

fedeortegariba/bsc-bio-ehr-es-fted-text-cl

bsc-bio-ehr-es-fted-text-cl