Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
1.0969	0.04	100	1.0991	0.4109	0.4964
1.0764	0.08	200	1.0768	0.5217	0.5971
0.955	0.12	300	0.9313	0.5802	0.6691
0.8137	0.17	400	0.8927	0.5864	0.6475
0.7837	0.21	500	0.8711	0.6238	0.6475
0.7234	0.25	600	0.9953	0.5641	0.6475
0.6983	0.29	700	0.9111	0.6226	0.6475
0.6574	0.33	800	0.8557	0.6686	0.6835
0.6653	0.37	900	0.7925	0.7087	0.7122
0.6444	0.41	1000	0.8338	0.7056	0.7122
0.6155	0.46	1100	0.8339	0.7257	0.7338
0.5726	0.5	1200	0.8078	0.7140	0.7194
0.6279	0.54	1300	0.9534	0.6917	0.7050
0.6083	0.58	1400	0.9515	0.6914	0.7050
0.5525	0.62	1500	0.9281	0.6846	0.7050
0.6849	0.66	1600	0.8352	0.6917	0.7050
0.5924	0.7	1700	1.0702	0.6602	0.6906
0.5614	0.75	1800	0.9689	0.6801	0.6978
0.5936	0.79	1900	1.0179	0.6896	0.7050
0.5582	0.83	2000	0.8858	0.7320	0.7410
0.5479	0.87	2100	0.9373	0.7030	0.7122
0.6278	0.91	2200	0.8694	0.6858	0.6978
0.4819	0.95	2300	0.9440	0.7074	0.7194
0.5425	0.99	2400	1.0661	0.6765	0.6906
0.5804	1.04	2500	0.8904	0.7189	0.7266
0.5025	1.08	2600	1.0105	0.6886	0.7050
0.5148	1.12	2700	0.9934	0.7076	0.7194
0.5359	1.16	2800	0.9249	0.7291	0.7410
0.5002	1.2	2900	0.7503	0.7047	0.7050
0.4563	1.24	3000	0.8149	0.7230	0.7266
0.4837	1.28	3100	0.8956	0.7125	0.7194
0.4486	1.33	3200	0.9013	0.7110	0.7194
0.4721	1.37	3300	1.0545	0.7142	0.7266
0.5482	1.41	3400	1.0139	0.7014	0.7122
0.4488	1.45	3500	0.9427	0.7162	0.7266
0.4859	1.49	3600	1.1337	0.7074	0.7194
0.504	1.53	3700	1.0299	0.7178	0.7266
0.4555	1.57	3800	0.8830	0.7273	0.7338
0.502	1.62	3900	1.0340	0.7142	0.7266
0.5131	1.66	4000	1.0997	0.7031	0.7194
0.5208	1.7	4100	1.0845	0.7025	0.7194
0.4329	1.74	4200	1.0553	0.7132	0.7266
0.4612	1.78	4300	1.0458	0.7074	0.7194
0.4857	1.82	4400	0.9425	0.7120	0.7194
0.4986	1.86	4500	0.9965	0.7237	0.7338
0.4066	1.91	4600	0.9520	0.7041	0.7122
0.4638	1.95	4700	0.9558	0.6979	0.7050
0.4541	1.99	4800	0.9808	0.7036	0.7122

Framework versions

Transformers 4.38.1
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2

gentilrenard/multi-e5-small_lmd-comments_v1

multi-e5-small_lmd-comments_v1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gentilrenard/
multi-e5-small_lmd-comments_v1