Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.3497	1.0	69	1.2944	0.5376	0.4665	0.6374	0.5376
1.2023	2.0	138	1.0370	0.7056	0.6745	0.7458	0.7056
0.9289	3.0	207	0.7437	0.8121	0.8082	0.8117	0.8121
0.6932	4.0	276	0.5717	0.8445	0.8428	0.8434	0.8445
0.5613	5.0	345	0.4888	0.8580	0.8572	0.8573	0.8580
0.469	6.0	414	0.4401	0.8633	0.8625	0.8623	0.8633
0.4176	7.0	483	0.4156	0.8653	0.8646	0.8644	0.8653
0.3724	8.0	552	0.4001	0.8706	0.8700	0.8699	0.8706
0.3427	9.0	621	0.3972	0.8706	0.8698	0.8701	0.8706
0.3243	10.0	690	0.3898	0.8737	0.8729	0.8736	0.8737
0.3039	11.0	759	0.3887	0.8716	0.8710	0.8717	0.8716
0.2803	12.0	828	0.3841	0.8716	0.8709	0.8709	0.8716
0.264	13.0	897	0.3872	0.8758	0.8753	0.8758	0.8758
0.2607	14.0	966	0.3837	0.8747	0.8743	0.8741	0.8747
0.2437	15.0	1035	0.3893	0.8716	0.8710	0.8712	0.8716
0.2358	16.0	1104	0.3867	0.8695	0.8691	0.8690	0.8695
0.2278	17.0	1173	0.3886	0.8737	0.8732	0.8732	0.8737
0.2143	18.0	1242	0.3902	0.8727	0.8720	0.8718	0.8727

mmillet/rubert-tiny2_best_finetuned_emotion_experiment_augmented_anger_fear

rubert-tiny2_best_finetuned_emotion_experiment_augmented_anger_fear