Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.7794	1.0	342	0.5844	0.7357	0.6625	0.5084	0.9508
0.5228	2.0	684	0.4504	0.8588	0.7793	0.6795	0.9133
0.4184	3.0	1026	0.3897	0.8957	0.8242	0.7627	0.8963
0.3696	4.0	1368	0.3621	0.9083	0.8423	0.7937	0.8972
0.3354	5.0	1710	0.3667	0.9064	0.8369	0.7976	0.8803
0.3079	6.0	2052	0.3525	0.9122	0.8459	0.8118	0.8829
0.2927	7.0	2394	0.3373	0.9181	0.8552	0.8260	0.8865
0.2741	8.0	2736	0.3219	0.9252	0.8668	0.8423	0.8928
0.2627	9.0	3078	0.3576	0.9147	0.8481	0.8245	0.8731
0.2528	10.0	3420	0.3306	0.9266	0.8685	0.8496	0.8883
0.2398	11.0	3762	0.3336	0.9281	0.8703	0.8564	0.8847
0.2318	12.0	4104	0.3289	0.9308	0.8751	0.8615	0.8892
0.2234	13.0	4446	0.3438	0.9271	0.8683	0.8559	0.8811
0.2169	14.0	4788	0.3311	0.9327	0.8787	0.8643	0.8937
0.2126	15.0	5130	0.3444	0.9288	0.8716	0.8580	0.8856
0.2078	16.0	5472	0.3442	0.9298	0.8734	0.8597	0.8874
0.206	17.0	5814	0.3520	0.9281	0.8699	0.8589	0.8811
0.1986	18.0	6156	0.3473	0.9305	0.8743	0.8632	0.8856
0.1958	19.0	6498	0.3502	0.9300	0.8732	0.8636	0.8829
0.1958	20.0	6840	0.3517	0.9298	0.8728	0.8629	0.8829

alex-miller/curated-gender-equality-weighted

curated-gender-equality-weighted