dif_metric_amazon_kindle_sentiment_analysis

denise227/dif_metric_amazon_kindle_sentiment_analysis

dif_metric_amazon_kindle_sentiment_analysis is a text classification model from denise227. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Apr 14, 2024
Updated: Apr 14, 2024
SHA: 6a37af0d

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Base models

Model card

From the Hugging Face model README

dif_metric_amazon_kindle_sentiment_analysis

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

Loss: 1.2119
Accuracy: 0.6

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: 2e-05
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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4993	0.02	10	1.0476	0.5808
0.5086	0.03	20	1.0657	0.5808
0.4702	0.05	30	1.0823	0.58
0.5238	0.07	40	1.1426	0.5608
0.4799	0.08	50	1.0619	0.5858
0.4808	0.1	60	1.1120	0.585
0.463	0.12	70	1.0674	0.5758
0.3872	0.13	80	1.1671	0.5792
0.4644	0.15	90	1.1096	0.575
0.4499	0.17	100	1.1601	0.575
0.3699	0.18	110	1.2459	0.565
0.4226	0.2	120	1.2242	0.57
0.6827	0.22	130	1.1437	0.59
0.633	0.23	140	1.3094	0.5467
0.4759	0.25	150	1.4381	0.5217
0.6485	0.27	160	1.1986	0.5542
0.4229	0.28	170	1.2395	0.5642
0.3618	0.3	180	1.2444	0.5567
0.5288	0.32	190	1.2414	0.5733
0.3946	0.33	200	1.2790	0.5675
0.3213	0.35	210	1.2749	0.57
0.4933	0.37	220	1.2454	0.5717
0.3368	0.38	230	1.3095	0.5625
0.428	0.4	240	1.2191	0.5675
0.3233	0.42	250	1.2650	0.5767
0.4256	0.43	260	1.2431	0.5875
0.505	0.45	270	1.2852	0.575
0.3405	0.47	280	1.2753	0.58
0.2997	0.48	290	1.2355	0.5833
0.3166	0.5	300	1.2394	0.5833
0.3945	0.52	310	1.2072	0.585
0.3944	0.53	320	1.2370	0.5833
0.4107	0.55	330	1.2283	0.5808
0.2498	0.57	340	1.2782	0.5775
0.3608	0.58	350	1.4234	0.565
0.4436	0.6	360	1.2708	0.5875
0.3745	0.62	370	1.2782	0.5783
0.3468	0.63	380	1.3724	0.5725
0.3561	0.65	390	1.2847	0.5883
0.3938	0.67	400	1.3866	0.5658
0.436	0.68	410	1.3286	0.5842
0.2518	0.7	420	1.3983	0.57
0.3923	0.72	430	1.4077	0.5575
0.368	0.73	440	1.3139	0.5775
0.4665	0.75	450	1.3430	0.5817
0.2811	0.77	460	1.3220	0.5858
0.2383	0.78	470	1.3196	0.5908
0.3638	0.8	480	1.3141	0.59
0.4298	0.82	490	1.3613	0.5867
0.3621	0.83	500	1.5250	0.5267
0.3613	0.85	510	1.3598	0.5842
0.3825	0.87	520	1.4080	0.5692
0.4243	0.88	530	1.3791	0.5875
0.4869	0.9	540	1.3808	0.5933
0.7625	0.92	550	1.3123	0.585
0.9794	0.93	560	1.2532	0.5925
0.6095	0.95	570	1.2624	0.5858
0.806	0.97	580	1.2222	0.5733
0.7479	0.98	590	1.1705	0.5767
0.6744	1.0	600	1.1430	0.5775
0.3205	1.02	610	1.1521	0.5808
0.4012	1.03	620	1.1715	0.6
0.4163	1.05	630	1.2237	0.5917
0.3824	1.07	640	1.2230	0.6008
0.4983	1.08	650	1.2200	0.5933
0.3678	1.1	660	1.2375	0.5908
0.4142	1.12	670	1.2434	0.5917
0.3852	1.13	680	1.2189	0.6075
0.3486	1.15	690	1.2383	0.595
0.436	1.17	700	1.2367	0.5933
0.3755	1.18	710	1.2292	0.5983
0.3124	1.2	720	1.2289	0.5983
0.4066	1.22	730	1.2193	0.5958
0.3882	1.23	740	1.2229	0.6025
0.4264	1.25	750	1.2066	0.6
0.382	1.27	760	1.2401	0.5867
0.4083	1.28	770	1.2310	0.5925
0.4244	1.3	780	1.2325	0.5942
0.3663	1.32	790	1.2371	0.59
0.3024	1.33	800	1.2646	0.5833
0.4253	1.35	810	1.2577	0.585
0.3527	1.37	820	1.2507	0.5867
0.354	1.38	830	1.2679	0.585
0.3585	1.4	840	1.3151	0.5942
0.4061	1.42	850	1.2708	0.5858
0.3498	1.43	860	1.2619	0.5892
0.4252	1.45	870	1.2518	0.5858
0.4091	1.47	880	1.2544	0.5742
0.2835	1.48	890	1.2472	0.585
0.3067	1.5	900	1.2494	0.59
0.4689	1.52	910	1.2516	0.59
0.5256	1.53	920	1.2403	0.5942
0.4434	1.55	930	1.2403	0.5933
0.4597	1.57	940	1.2355	0.5867
0.4791	1.58	950	1.2302	0.5992
0.3919	1.6	960	1.2243	0.5967
0.408	1.62	970	1.2207	0.5983
0.3767	1.63	980	1.2207	0.5942
0.4726	1.65	990	1.2226	0.5867
0.4926	1.67	1000	1.2121	0.5992
0.4534	1.68	1010	1.2118	0.5975
0.3774	1.7	1020	1.2113	0.5992
0.4451	1.72	1030	1.2110	0.6033
0.2872	1.73	1040	1.2124	0.6042
0.4425	1.75	1050	1.2145	0.5983
0.4125	1.77	1060	1.2175	0.5983
0.3929	1.78	1070	1.2183	0.6075
0.5153	1.8	1080	1.2177	0.6058
0.4643	1.82	1090	1.2179	0.6033
0.4116	1.83	1100	1.2192	0.6033
0.3701	1.85	1110	1.2198	0.6025
0.73	1.87	1120	1.2195	0.5983
0.4559	1.88	1130	1.2172	0.6
0.5021	1.9	1140	1.2151	0.5975
0.54	1.92	1150	1.2136	0.5958
0.5492	1.93	1160	1.2136	0.5967
0.524	1.95	1170	1.2132	0.6
0.4983	1.97	1180	1.2127	0.5975
0.6899	1.98	1190	1.2121	0.6
0.4692	2.0	1200	1.2119	0.6

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Apr 14, 2024
Updated: Apr 14, 2024