metadata

tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: roberta-base-culinary-finetuned
    results: []

roberta-base-culinary-finetuned

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

Model description

More information needed

More information needed

More information needed

The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	F1
0.1803	0.11	500	0.1939	0.9611
0.1543	0.22	1000	0.1364	0.9669
0.1213	0.32	1500	0.1487	0.9728
0.1079	0.43	2000	0.0855	0.9773
0.0975	0.54	2500	0.0844	0.9831
0.0855	0.65	3000	0.0785	0.9831
0.0844	0.76	3500	0.0679	0.9857
0.0793	0.86	4000	0.0489	0.9890
0.0864	0.97	4500	0.0399	0.9903
0.049	1.08	5000	0.0528	0.9890
0.0353	1.19	5500	0.0635	0.9877
0.0321	1.3	6000	0.0542	0.9903
0.0311	1.41	6500	0.0559	0.9896
0.0315	1.51	7000	0.0736	0.9857
0.04	1.62	7500	0.0648	0.9909
0.0265	1.73	8000	0.0608	0.9909
0.0443	1.84	8500	0.0617	0.9883
0.0443	1.95	9000	0.0555	0.9896
0.0235	2.05	9500	0.0608	0.9903
0.0139	2.16	10000	0.0613	0.9922
0.0126	2.27	10500	0.0739	0.9903
0.0164	2.38	11000	0.0679	0.9903
0.0172	2.49	11500	0.0606	0.9922
0.0175	2.59	12000	0.0442	0.9942
0.01	2.7	12500	0.0661	0.9916
0.0059	2.81	13000	0.0659	0.9929
0.0216	2.92	13500	0.0504	0.9929
0.0123	3.03	14000	0.0584	0.9929
0.0047	3.14	14500	0.0573	0.9929
0.0123	3.24	15000	0.0511	0.9935
0.0027	3.35	15500	0.0579	0.9942
0.0025	3.46	16000	0.0602	0.9935
0.0051	3.57	16500	0.0598	0.9935
0.0044	3.68	17000	0.0617	0.9929
0.0061	3.78	17500	0.0634	0.9935
0.0048	3.89	18000	0.0672	0.9929
0.0078	4.0	18500	0.0657	0.9929