Intent-classification-BERT-cased-Ashu

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

• Loss: 0.1960
• Accuracy: 0.9321

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0002
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.6354	0.24	10	1.3680	0.3478
1.2714	0.49	20	1.0836	0.5590
1.1593	0.73	30	0.7338	0.8012
0.6734	0.98	40	0.4365	0.8882
0.554	1.22	50	0.6694	0.8385
0.5863	1.46	60	0.4113	0.8385
0.3894	1.71	70	0.2667	0.9006
0.3458	1.95	80	0.3299	0.8882
0.3338	2.2	90	0.3247	0.8882
0.2073	2.44	100	0.2303	0.8944
0.2844	2.68	110	0.2886	0.8944
0.4828	2.93	120	0.2475	0.9006
0.2294	3.17	130	0.2751	0.8820
0.3103	3.41	140	0.2409	0.8696
0.1972	3.66	150	0.2038	0.9130
0.1808	3.9	160	0.2399	0.9068
0.1904	4.15	170	0.2559	0.9068
0.2458	4.39	180	0.5942	0.8634
0.1777	4.63	190	0.3048	0.8820
0.2233	4.88	200	0.2170	0.9130
0.2446	5.12	210	0.3414	0.8758
0.1631	5.37	220	0.3601	0.8882
0.3007	5.61	230	0.4856	0.8571
0.2979	5.85	240	0.7301	0.8447
0.3355	6.1	250	0.3030	0.8944
0.2137	6.34	260	0.4366	0.8820
0.3109	6.59	270	0.3117	0.8944
0.1863	6.83	280	0.4387	0.8758
0.2912	7.07	290	0.2516	0.9006
0.1621	7.32	300	0.3174	0.9006
0.2598	7.56	310	0.6467	0.8385
0.351	7.8	320	0.2943	0.8820
0.3232	8.05	330	0.2908	0.8944
0.1534	8.29	340	0.3321	0.8944
0.208	8.54	350	0.4615	0.8447
0.3685	8.78	360	0.4475	0.8696
0.1663	9.02	370	0.4067	0.8696
0.2267	9.27	380	0.4081	0.8758
0.2486	9.51	390	0.5971	0.8509
0.4295	9.76	400	0.2917	0.8882
0.2481	10.0	410	0.3792	0.8820
0.1681	10.24	420	0.3793	0.8882
0.1313	10.49	430	0.3035	0.9006
0.3188	10.73	440	0.3317	0.8758
0.2266	10.98	450	0.4534	0.8696
0.1728	11.22	460	0.3922	0.8882
0.1655	11.46	470	0.2906	0.8882
0.1764	11.71	480	0.3753	0.8758
0.1654	11.95	490	0.3411	0.8820
0.114	12.2	500	0.3693	0.8758
0.2119	12.44	510	0.4721	0.8820
0.1655	12.68	520	0.5551	0.8758
0.2329	12.93	530	0.4987	0.8758
0.2048	13.17	540	0.4264	0.8758
0.2365	13.41	550	0.3291	0.9006
0.1067	13.66	560	0.3542	0.9006
0.1939	13.9	570	0.3957	0.9006
0.2257	14.15	580	0.3690	0.8882
0.1853	14.39	590	0.3377	0.9006
0.2486	14.63	600	0.2423	0.9068
0.147	14.88	610	0.3141	0.8882
0.1639	15.12	620	0.4718	0.8758
0.151	15.37	630	0.6900	0.8571
0.2909	15.61	640	0.3900	0.9006
0.2273	15.85	650	0.3972	0.8820
0.2317	16.1	660	0.3208	0.8944
0.2005	16.34	670	0.3355	0.8882
0.1807	16.59	680	0.4310	0.8882
0.216	16.83	690	0.4881	0.8882
0.1307	17.07	700	0.3590	0.8882
0.234	17.32	710	0.3503	0.8758
0.224	17.56	720	0.3790	0.8758
0.1708	17.8	730	0.2696	0.8944
0.1848	18.05	740	0.2631	0.8944
0.1799	18.29	750	0.2867	0.9006
0.1882	18.54	760	0.4595	0.8758
0.1072	18.78	770	0.3914	0.8944
0.2072	19.02	780	0.3018	0.9006
0.2289	19.27	790	0.2462	0.9006
0.1597	19.51	800	0.2632	0.9068
0.1475	19.76	810	0.3012	0.8944
0.1691	20.0	820	0.2272	0.9006
0.1339	20.24	830	0.2947	0.8882
0.1247	20.49	840	0.3514	0.9068
0.2072	20.73	850	0.3281	0.8758
0.1379	20.98	860	0.3696	0.9006
0.123	21.22	870	0.4604	0.8944
0.1697	21.46	880	0.4491	0.8820
0.1613	21.71	890	0.3338	0.9006
0.1816	21.95	900	0.3421	0.9006
0.2516	22.2	910	0.3395	0.9006
0.1367	22.44	920	0.3416	0.9006
0.1148	22.68	930	0.3901	0.8944
0.123	22.93	940	0.4092	0.8944
0.0922	23.17	950	0.4680	0.8820
0.1294	23.41	960	0.4898	0.8944
0.1986	23.66	970	0.4286	0.8882
0.175	23.9	980	0.4919	0.8882
0.1264	24.15	990	0.5121	0.8944
0.1454	24.39	1000	0.5529	0.8944
0.1986	24.63	1010	0.4504	0.8944
0.2549	24.88	1020	0.3442	0.8944
0.1878	25.12	1030	0.3414	0.8882
0.1313	25.37	1040	0.3944	0.8758
0.0957	25.61	1050	0.4231	0.8820
0.1751	25.85	1060	0.4765	0.8820
0.1389	26.1	1070	0.4927	0.8820
0.1038	26.34	1080	0.4923	0.8820
0.1371	26.59	1090	0.4848	0.8820
0.1576	26.83	1100	0.4765	0.8820
0.1539	27.07	1110	0.4926	0.8820
0.1742	27.32	1120	0.4749	0.8820
0.1365	27.56	1130	0.4717	0.8820
0.1284	27.8	1140	0.4754	0.8820
0.0794	28.05	1150	0.4871	0.8820
0.0934	28.29	1160	0.5052	0.8820
0.1384	28.54	1170	0.5146	0.8820
0.1323	28.78	1180	0.5140	0.8820
0.1352	29.02	1190	0.5068	0.8820
0.1576	29.27	1200	0.5068	0.8758
0.1278	29.51	1210	0.5067	0.8758
0.1256	29.76	1220	0.5071	0.8758
0.0999	30.0	1230	0.5078	0.8758

Framework versions

• Transformers 4.38.2
• Pytorch 2.1.2
• Datasets 2.1.0
• Tokenizers 0.15.2