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ikura31/
results_2

Name: results_2
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results_2

This model is a fine-tuned version of distilbert/distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.1286	1.0	120	1.1322	0.3458	0.5471	0.3458	0.2569
1.007	2.0	240	1.1356	0.4625	0.4700	0.4625	0.4234
0.8347	3.0	360	1.2379	0.4292	0.4550	0.4292	0.3851
0.7291	4.0	480	1.4182	0.4583	0.4778	0.4583	0.4575
0.3339	5.0	600	1.9020	0.4792	0.4986	0.4792	0.4631
0.1862	6.0	720	2.3742	0.4708	0.4847	0.4708	0.4734
0.2639	7.0	840	2.9896	0.4542	0.4583	0.4542	0.4519
0.0691	8.0	960	3.6229	0.4583	0.4918	0.4583	0.4515
0.2158	9.0	1080	3.7731	0.4625	0.4741	0.4625	0.4595
0.1475	10.0	1200	4.1775	0.4667	0.4678	0.4667	0.4540
0.1593	11.0	1320	4.1295	0.45	0.4612	0.45	0.4453
0.0018	12.0	1440	4.2133	0.4417	0.4434	0.4417	0.4389
0.0006	13.0	1560	4.4056	0.4583	0.4736	0.4583	0.4567
0.0025	14.0	1680	4.6331	0.4667	0.4780	0.4667	0.4591
0.0001	15.0	1800	4.6897	0.4583	0.4582	0.4583	0.4530
0.0001	16.0	1920	4.6231	0.45	0.4549	0.45	0.4513
0.0003	17.0	2040	4.6506	0.4708	0.4706	0.4708	0.4695
0.0001	18.0	2160	4.6900	0.4708	0.4692	0.4708	0.4691
0.0001	19.0	2280	4.7095	0.4708	0.4695	0.4708	0.4657
0.0047	20.0	2400	4.7870	0.4625	0.4649	0.4625	0.4590
0.0001	21.0	2520	4.8568	0.4708	0.4697	0.4708	0.4687
0.0001	22.0	2640	4.9106	0.4708	0.4748	0.4708	0.4675
0.0001	23.0	2760	4.8998	0.4667	0.4699	0.4667	0.4627
0.0001	24.0	2880	4.9071	0.4708	0.4742	0.4708	0.4671