DeBERT_50K_steps

This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Hamming
0.2014	0.02	2500	0.0451	0.9902	0.0	0.0	0.0	0.0098
0.0373	0.04	5000	0.0297	0.9913	0.6879	0.2003	0.3102	0.0087
0.0286	0.06	7500	0.0250	0.9921	0.6965	0.3329	0.4505	0.0079
0.0253	0.08	10000	0.0233	0.9925	0.7038	0.4010	0.5109	0.0075
0.0234	0.1	12500	0.0217	0.9928	0.7085	0.4382	0.5415	0.0072
0.0223	0.12	15000	0.0208	0.9930	0.7229	0.4559	0.5591	0.0070
0.0213	0.14	17500	0.0205	0.9931	0.7255	0.4696	0.5701	0.0069
0.0206	0.16	20000	0.0196	0.9933	0.7325	0.4990	0.5936	0.0067
0.0203	0.18	22500	0.0191	0.9935	0.7368	0.5125	0.6045	0.0065
0.0196	0.2	25000	0.0188	0.9935	0.7354	0.5209	0.6098	0.0065
0.0195	0.22	27500	0.0185	0.9936	0.7415	0.5335	0.6205	0.0064
0.019	0.24	30000	0.0183	0.9936	0.7437	0.5296	0.6186	0.0064
0.0189	0.26	32500	0.0180	0.9938	0.7585	0.5304	0.6243	0.0062
0.0187	0.28	35000	0.0178	0.9938	0.7630	0.5342	0.6284	0.0062
0.0184	0.3	37500	0.0175	0.9939	0.7626	0.5457	0.6362	0.0061
0.0182	0.32	40000	0.0174	0.9939	0.7621	0.5451	0.6356	0.0061
0.0179	0.34	42500	0.0172	0.9940	0.7594	0.5563	0.6422	0.0060
0.0178	0.36	45000	0.0171	0.9940	0.7553	0.5633	0.6453	0.0060
0.0177	0.38	47500	0.0170	0.9941	0.7623	0.5680	0.6510	0.0059
0.0175	0.4	50000	0.0169	0.9941	0.7649	0.5670	0.6512	0.0059