distilbert-base-uncased-finetuned-customer-reviews

This model is a fine-tuned version of distilbert-base-uncased 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	F1
0.6594	1.0	17	0.6247	0.6667	0.0
0.6259	2.0	34	0.6059	0.6667	0.0
0.5948	3.0	51	0.5691	0.6925	0.2074
0.5516	4.0	68	0.5241	0.7701	0.5238
0.5022	5.0	85	0.4813	0.7989	0.6111
0.4698	6.0	102	0.4496	0.8276	0.6629
0.4179	7.0	119	0.4137	0.8563	0.7423
0.3801	8.0	136	0.3833	0.8764	0.7817
0.3396	9.0	153	0.3537	0.9023	0.8317
0.3042	10.0	170	0.3256	0.9109	0.8517
0.2743	11.0	187	0.3058	0.9195	0.8692
0.2472	12.0	204	0.2905	0.9195	0.8692
0.2251	13.0	221	0.2780	0.9167	0.8638
0.1979	14.0	238	0.2659	0.9224	0.8744
0.1864	15.0	255	0.2573	0.9224	0.8756
0.158	16.0	272	0.2470	0.9253	0.8807
0.1493	17.0	289	0.2357	0.9282	0.8869
0.1404	18.0	306	0.2352	0.9253	0.8807
0.1364	19.0	323	0.2294	0.9282	0.8858
0.1256	20.0	340	0.2225	0.9253	0.8807
0.12	21.0	357	0.2160	0.9253	0.8807
0.1177	22.0	374	0.2136	0.9253	0.8807
0.1115	23.0	391	0.2119	0.9253	0.8807
0.1084	24.0	408	0.2090	0.9310	0.8899
0.1062	25.0	425	0.2097	0.9253	0.8807
0.1078	26.0	442	0.2037	0.9253	0.8807
0.102	27.0	459	0.2047	0.9253	0.8807
0.1016	28.0	476	0.2025	0.9224	0.8756
0.0971	29.0	493	0.2033	0.9253	0.8807
0.0985	30.0	510	0.2025	0.9282	0.8858