added_token_resized_model_test_0825

This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0004
• Accuracy: 1.0000
• F1: 0.9981
• Precision: 0.9961
• Recall: 1.0

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 200

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	123	0.0578	0.9938	0.0	0.0	0.0
No log	2.0	246	0.0371	0.9938	0.0	0.0	0.0
No log	3.0	369	0.0358	0.9938	0.0	0.0	0.0
No log	4.0	492	0.0339	0.9938	0.0	0.0	0.0
0.0968	5.0	615	0.0329	0.9938	0.0	0.0	0.0
0.0968	6.0	738	0.0293	0.9938	0.0	0.0	0.0
0.0968	7.0	861	0.0257	0.9936	0.0223	0.2727	0.0116
0.0968	8.0	984	0.0243	0.9938	0.0	0.0	0.0
0.0299	9.0	1107	0.0239	0.9938	0.0	0.0	0.0
0.0299	10.0	1230	0.0249	0.9934	0.3089	0.4453	0.2364
0.0299	11.0	1353	0.0226	0.9938	0.0	0.0	0.0
0.0299	12.0	1476	0.0236	0.9938	0.1623	0.5	0.0969
0.0249	13.0	1599	0.0213	0.9935	0.0	0.0	0.0
0.0249	14.0	1722	0.0203	0.9939	0.1759	0.5510	0.1047
0.0249	15.0	1845	0.0190	0.9939	0.2025	0.5517	0.1240
0.0249	16.0	1968	0.0192	0.9938	0.0	0.0	0.0
0.0218	17.0	2091	0.0177	0.9942	0.1495	0.9130	0.0814
0.0218	18.0	2214	0.0178	0.9950	0.4607	0.7097	0.3411
0.0218	19.0	2337	0.0168	0.9948	0.4216	0.6964	0.3023
0.0218	20.0	2460	0.0171	0.9947	0.3323	0.8060	0.2093
0.0184	21.0	2583	0.0151	0.9953	0.4670	0.8019	0.3295
0.0184	22.0	2706	0.0144	0.9955	0.5131	0.7903	0.3798
0.0184	23.0	2829	0.0140	0.9955	0.5507	0.7308	0.4419
0.0184	24.0	2952	0.0144	0.9954	0.4863	0.8241	0.3450
0.016	25.0	3075	0.0131	0.9958	0.5940	0.7399	0.4961
0.016	26.0	3198	0.0133	0.9960	0.5951	0.8026	0.4729
0.016	27.0	3321	0.0134	0.9959	0.5947	0.7799	0.4806
0.016	28.0	3444	0.0124	0.9961	0.6165	0.7844	0.5078
0.0141	29.0	3567	0.0118	0.9961	0.6279	0.7849	0.5233
0.0141	30.0	3690	0.0114	0.9962	0.6165	0.8247	0.4922
0.0141	31.0	3813	0.0114	0.9960	0.6404	0.7374	0.5659
0.0141	32.0	3936	0.0116	0.9958	0.5865	0.7722	0.4729
0.013	33.0	4059	0.0105	0.9966	0.6847	0.8172	0.5891
0.013	34.0	4182	0.0099	0.9968	0.6968	0.8370	0.5969
0.013	35.0	4305	0.0109	0.9960	0.6224	0.7598	0.5271
0.013	36.0	4428	0.0094	0.9967	0.7054	0.7923	0.6357
0.0107	37.0	4551	0.0091	0.9967	0.6953	0.8324	0.5969
0.0107	38.0	4674	0.0090	0.9968	0.7061	0.8131	0.6240
0.0107	39.0	4797	0.0090	0.9968	0.7158	0.8128	0.6395
0.0107	40.0	4920	0.0086	0.9969	0.7205	0.825	0.6395
0.0104	41.0	5043	0.0081	0.9972	0.7417	0.8615	0.6512
0.0104	42.0	5166	0.0080	0.9972	0.7619	0.8178	0.7132
0.0104	43.0	5289	0.0083	0.9971	0.7463	0.8294	0.6783
0.0104	44.0	5412	0.0073	0.9975	0.7794	0.8708	0.7054
0.0087	45.0	5535	0.0072	0.9976	0.7851	0.9040	0.6938
0.0087	46.0	5658	0.0070	0.9977	0.8025	0.8761	0.7403
0.0087	47.0	5781	0.0093	0.9965	0.6883	0.7794	0.6163
0.0087	48.0	5904	0.0087	0.9967	0.6852	0.8506	0.5736
0.0099	49.0	6027	0.0081	0.9969	0.7351	0.7817	0.6938
0.0099	50.0	6150	0.0080	0.9969	0.7078	0.8611	0.6008
0.0099	51.0	6273	0.0075	0.9971	0.7424	0.85	0.6589
0.0099	52.0	6396	0.0076	0.9970	0.7389	0.8169	0.6744
0.0087	53.0	6519	0.0087	0.9969	0.7156	0.8385	0.6240
0.0087	54.0	6642	0.0092	0.9963	0.6308	0.8543	0.5
0.0087	55.0	6765	0.0082	0.9966	0.6887	0.8	0.6047
0.0087	56.0	6888	0.0078	0.9967	0.6882	0.8514	0.5775
0.0089	57.0	7011	0.0077	0.9970	0.7325	0.8434	0.6473
0.0089	58.0	7134	0.0077	0.9969	0.7221	0.8291	0.6395
0.0089	59.0	7257	0.0075	0.9971	0.7375	0.8374	0.6589
0.0089	60.0	7380	0.0074	0.9973	0.7559	0.8537	0.6783
0.0074	61.0	7503	0.0083	0.9967	0.6822	0.8588	0.5659
0.0074	62.0	7626	0.0079	0.9971	0.7341	0.8477	0.6473
0.0074	63.0	7749	0.0075	0.9970	0.7089	0.8988	0.5853
0.0074	64.0	7872	0.0078	0.9970	0.7156	0.8764	0.6047
0.0074	65.0	7995	0.0075	0.9972	0.7473	0.8629	0.6589
0.0077	66.0	8118	0.0070	0.9972	0.7516	0.8488	0.6744
0.0077	67.0	8241	0.0070	0.9973	0.7603	0.8585	0.6822
0.0077	68.0	8364	0.0066	0.9974	0.7662	0.8676	0.6860
0.0077	69.0	8487	0.0070	0.9972	0.7421	0.8913	0.6357
0.0065	70.0	8610	0.0073	0.9971	0.7170	0.9157	0.5891
0.0065	71.0	8733	0.0068	0.9972	0.7361	0.9138	0.6163
0.0065	72.0	8856	0.0069	0.9974	0.7682	0.8606	0.6938
0.0065	73.0	8979	0.0070	0.9974	0.7735	0.8619	0.7016
0.0062	74.0	9102	0.0070	0.9974	0.7735	0.8619	0.7016
0.0062	75.0	9225	0.0064	0.9974	0.7745	0.8585	0.7054
0.0062	76.0	9348	0.0067	0.9973	0.7588	0.8737	0.6705
0.0062	77.0	9471	0.0068	0.9974	0.7483	0.9257	0.6279
0.0056	78.0	9594	0.0074	0.9975	0.7689	0.9010	0.6705
0.0056	79.0	9717	0.0063	0.9975	0.7839	0.8645	0.7171
0.0056	80.0	9840	0.0061	0.9975	0.7664	0.9235	0.6550
0.0056	81.0	9963	0.0060	0.9976	0.7863	0.8762	0.7132
0.0058	82.0	10086	0.0060	0.9976	0.7889	0.8768	0.7171
0.0058	83.0	10209	0.0067	0.9975	0.7664	0.9235	0.6550
0.0058	84.0	10332	0.0063	0.9976	0.7898	0.8732	0.7209
0.0058	85.0	10455	0.0077	0.9971	0.7136	0.9545	0.5698
0.005	86.0	10578	0.0090	0.9971	0.7076	0.9664	0.5581
0.005	87.0	10701	0.0113	0.9972	0.7246	0.9615	0.5814
0.005	88.0	10824	0.0089	0.9973	0.7316	0.9448	0.5969
0.005	89.0	10947	0.0118	0.9972	0.7202	0.9673	0.5736
0.0048	90.0	11070	0.0127	0.9973	0.7338	0.9623	0.5930
0.0048	91.0	11193	0.0099	0.9974	0.7404	0.9747	0.5969
0.0048	92.0	11316	0.0107	0.9974	0.7373	0.9745	0.5930
0.0048	93.0	11439	0.0097	0.9975	0.7588	0.9586	0.6279
0.0046	94.0	11562	0.0098	0.9974	0.7523	0.9213	0.6357
0.0046	95.0	11685	0.0039	0.9986	0.8792	0.9505	0.8178
0.0046	96.0	11808	0.0037	0.9986	0.8824	0.9633	0.8140
0.0046	97.0	11931	0.0032	0.9989	0.9105	0.8951	0.9264
0.0037	98.0	12054	0.0030	0.9988	0.9052	0.9035	0.9070
0.0037	99.0	12177	0.0030	0.9989	0.9127	0.9350	0.8915
0.0037	100.0	12300	0.0030	0.9990	0.9189	0.9154	0.9225
0.0037	101.0	12423	0.0027	0.9991	0.924	0.9545	0.8953
0.0035	102.0	12546	0.0086	0.9984	0.8578	0.9660	0.7713
0.0035	103.0	12669	0.0084	0.9984	0.8650	0.9491	0.7946
0.0035	104.0	12792	0.0084	0.9985	0.8686	0.9579	0.7946
0.0035	105.0	12915	0.0088	0.9983	0.8530	0.9156	0.7984
0.0032	106.0	13038	0.0086	0.9983	0.8468	0.9387	0.7713
0.0032	107.0	13161	0.0025	0.9991	0.9276	0.9368	0.9186
0.0032	108.0	13284	0.0024	0.9991	0.9300	0.9336	0.9264
0.0032	109.0	13407	0.0024	0.9991	0.9261	0.9547	0.8992
0.0031	110.0	13530	0.0024	0.9991	0.9270	0.9438	0.9109
0.0031	111.0	13653	0.0023	0.9993	0.9409	0.956	0.9264
0.0031	112.0	13776	0.0024	0.9991	0.9294	0.9405	0.9186
0.0031	113.0	13899	0.0022	0.9993	0.9414	0.9488	0.9341
0.0027	114.0	14022	0.0021	0.9993	0.9432	0.9526	0.9341
0.0027	115.0	14145	0.0023	0.9991	0.9264	0.9510	0.9031
0.0027	116.0	14268	0.0022	0.9993	0.9425	0.9318	0.9535
0.0027	117.0	14391	0.0022	0.9991	0.9295	0.9139	0.9457
0.0026	118.0	14514	0.0020	0.9992	0.9403	0.9349	0.9457
0.0026	119.0	14637	0.0018	0.9994	0.9496	0.9496	0.9496
0.0026	120.0	14760	0.0018	0.9993	0.9478	0.9459	0.9496
0.0026	121.0	14883	0.0020	0.9993	0.9439	0.9421	0.9457
0.0024	122.0	15006	0.0021	0.9992	0.9391	0.9522	0.9264
0.0024	123.0	15129	0.0017	0.9995	0.9614	0.9577	0.9651
0.0024	124.0	15252	0.0017	0.9995	0.9595	0.9540	0.9651
0.0024	125.0	15375	0.0016	0.9995	0.9609	0.9685	0.9535
0.0024	126.0	15498	0.0018	0.9994	0.9520	0.9430	0.9612
0.0022	127.0	15621	0.0016	0.9995	0.9577	0.9504	0.9651
0.0022	128.0	15744	0.0017	0.9994	0.9557	0.9502	0.9612
0.0022	129.0	15867	0.0015	0.9996	0.9651	0.9651	0.9651
0.0022	130.0	15990	0.0015	0.9996	0.9655	0.9545	0.9767
0.002	131.0	16113	0.0014	0.9996	0.9670	0.9689	0.9651
0.002	132.0	16236	0.0015	0.9995	0.9580	0.9436	0.9729
0.002	133.0	16359	0.0014	0.9996	0.9690	0.9690	0.9690
0.002	134.0	16482	0.0013	0.9996	0.9689	0.9727	0.9651
0.0018	135.0	16605	0.0013	0.9996	0.9654	0.9580	0.9729
0.0018	136.0	16728	0.0013	0.9996	0.9650	0.9688	0.9612
0.0018	137.0	16851	0.0013	0.9996	0.9670	0.9689	0.9651
0.0018	138.0	16974	0.0012	0.9996	0.9691	0.9654	0.9729
0.0016	139.0	17097	0.0012	0.9996	0.9674	0.9582	0.9767
0.0016	140.0	17220	0.0011	0.9997	0.9750	0.9693	0.9806
0.0016	141.0	17343	0.0011	0.9998	0.9826	0.9807	0.9845
0.0016	142.0	17466	0.0011	0.9996	0.9712	0.9620	0.9806
0.0015	143.0	17589	0.0011	0.9997	0.9746	0.9842	0.9651
0.0015	144.0	17712	0.0012	0.9997	0.9752	0.9588	0.9922
0.0015	145.0	17835	0.0010	0.9997	0.9787	0.9768	0.9806
0.0015	146.0	17958	0.0009	0.9998	0.9845	0.9845	0.9845
0.0014	147.0	18081	0.0010	0.9997	0.9747	0.9804	0.9690
0.0014	148.0	18204	0.0009	0.9999	0.9883	0.9922	0.9845
0.0014	149.0	18327	0.0010	0.9997	0.9786	0.9843	0.9729
0.0014	150.0	18450	0.0009	0.9998	0.9827	0.9770	0.9884
0.0012	151.0	18573	0.0009	0.9999	0.9884	0.9884	0.9884
0.0012	152.0	18696	0.0008	0.9998	0.9864	0.9922	0.9806
0.0012	153.0	18819	0.0008	0.9999	0.9903	0.9884	0.9922
0.0012	154.0	18942	0.0008	0.9999	0.9884	0.9846	0.9922
0.0012	155.0	19065	0.0008	0.9999	0.9884	0.9846	0.9922
0.0012	156.0	19188	0.0007	0.9999	0.9885	0.9809	0.9961
0.0012	157.0	19311	0.0007	0.9999	0.9923	0.9885	0.9961
0.0012	158.0	19434	0.0007	0.9999	0.9903	0.9884	0.9922
0.001	159.0	19557	0.0007	0.9999	0.9884	0.9846	0.9922
0.001	160.0	19680	0.0007	0.9999	0.9903	0.9922	0.9884
0.001	161.0	19803	0.0007	0.9999	0.9922	0.9922	0.9922
0.001	162.0	19926	0.0006	0.9999	0.9922	0.9961	0.9884
0.0009	163.0	20049	0.0008	0.9998	0.9806	0.9806	0.9806
0.0009	164.0	20172	0.0006	0.9999	0.9903	0.9884	0.9922
0.0009	165.0	20295	0.0006	0.9999	0.9942	0.9961	0.9922
0.0009	166.0	20418	0.0006	1.0000	0.9961	0.9961	0.9961
0.0008	167.0	20541	0.0006	0.9999	0.9942	0.9923	0.9961
0.0008	168.0	20664	0.0006	0.9999	0.9922	0.9922	0.9922
0.0008	169.0	20787	0.0006	0.9999	0.9942	1.0	0.9884
0.0008	170.0	20910	0.0006	1.0000	0.9981	0.9961	1.0
0.0009	171.0	21033	0.0006	0.9999	0.9942	0.9923	0.9961
0.0009	172.0	21156	0.0005	1.0000	0.9961	0.9961	0.9961
0.0009	173.0	21279	0.0005	1.0000	0.9961	0.9961	0.9961
0.0009	174.0	21402	0.0005	1.0000	0.9961	0.9961	0.9961
0.0007	175.0	21525	0.0005	1.0000	0.9961	0.9961	0.9961
0.0007	176.0	21648	0.0005	1.0000	0.9981	0.9961	1.0
0.0007	177.0	21771	0.0005	1.0000	0.9961	0.9961	0.9961
0.0007	178.0	21894	0.0005	1.0000	0.9981	0.9961	1.0
0.0007	179.0	22017	0.0005	1.0000	0.9961	0.9961	0.9961
0.0007	180.0	22140	0.0005	1.0000	0.9981	0.9961	1.0
0.0007	181.0	22263	0.0005	1.0000	0.9981	0.9961	1.0
0.0007	182.0	22386	0.0004	1.0000	0.9981	0.9961	1.0
0.0007	183.0	22509	0.0004	1.0000	0.9981	0.9961	1.0
0.0007	184.0	22632	0.0004	1.0000	0.9981	0.9961	1.0
0.0007	185.0	22755	0.0005	1.0000	0.9961	0.9923	1.0
0.0007	186.0	22878	0.0004	1.0	1.0	1.0	1.0
0.0006	187.0	23001	0.0004	1.0	1.0	1.0	1.0
0.0006	188.0	23124	0.0004	1.0000	0.9981	0.9961	1.0
0.0006	189.0	23247	0.0004	1.0	1.0	1.0	1.0
0.0006	190.0	23370	0.0004	1.0000	0.9981	0.9961	1.0
0.0006	191.0	23493	0.0004	1.0000	0.9981	0.9961	1.0
0.0006	192.0	23616	0.0004	1.0000	0.9981	0.9961	1.0
0.0006	193.0	23739	0.0004	1.0000	0.9981	0.9961	1.0
0.0006	194.0	23862	0.0004	1.0000	0.9981	0.9961	1.0
0.0006	195.0	23985	0.0004	1.0000	0.9981	0.9961	1.0
0.0006	196.0	24108	0.0004	1.0000	0.9981	0.9961	1.0
0.0006	197.0	24231	0.0004	1.0000	0.9981	0.9961	1.0
0.0006	198.0	24354	0.0004	1.0000	0.9981	0.9961	1.0
0.0006	199.0	24477	0.0004	1.0000	0.9981	0.9961	1.0
0.0006	200.0	24600	0.0004	1.0000	0.9981	0.9961	1.0

Framework versions

• Transformers 4.39.2
• Pytorch 2.2.2+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2