bankstatementmodelver8

This model is a fine-tuned version of deepset/roberta-base-squad2 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0

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: 16
• eval_batch_size: 11
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 150

Training results

Training Loss	Epoch	Step	Validation Loss
0.1067	1.0	981	0.0322
0.0357	2.0	1962	0.0228
0.0239	3.0	2943	0.0172
0.0253	4.0	3924	0.0158
0.0206	5.0	4905	0.0127
0.0168	6.0	5886	0.0160
0.0158	7.0	6867	0.0154
0.0169	8.0	7848	0.0134
0.0162	9.0	8829	0.0081
0.0162	10.0	9810	0.0101
0.0126	11.0	10791	0.0082
0.0128	12.0	11772	0.0080
0.013	13.0	12753	0.0119
0.0117	14.0	13734	0.0105
0.0117	15.0	14715	0.0106
0.0112	16.0	15696	0.0100
0.0103	17.0	16677	0.0078
0.0075	18.0	17658	0.0060
0.0057	19.0	18639	0.0088
0.0077	20.0	19620	0.0076
0.006	21.0	20601	0.0149
0.0065	22.0	21582	0.0062
0.0093	23.0	22563	0.0081
0.0045	24.0	23544	0.0054
0.005	25.0	24525	0.0048
0.0068	26.0	25506	0.0122
0.0063	27.0	26487	0.0038
0.0043	28.0	27468	0.0063
0.0055	29.0	28449	0.0096
0.0034	30.0	29430	0.0045
0.0033	31.0	30411	0.0025
0.0027	32.0	31392	0.0047
0.002	33.0	32373	0.0053
0.0055	34.0	33354	0.0026
0.0044	35.0	34335	0.0010
0.0047	36.0	35316	0.0008
0.0019	37.0	36297	0.0011
0.0006	38.0	37278	0.0030
0.0015	39.0	38259	0.0010
0.0005	40.0	39240	0.0008
0.0018	41.0	40221	0.0001
0.0026	42.0	41202	0.0017
0.0	43.0	42183	0.0002
0.002	44.0	43164	0.0009
0.0012	45.0	44145	0.0000
0.0018	46.0	45126	0.0110
0.0006	47.0	46107	0.0018
0.0016	48.0	47088	0.0000
0.0017	49.0	48069	0.0000
0.0014	50.0	49050	0.0000
0.0001	51.0	50031	0.0000
0.0018	52.0	51012	0.0020
0.0001	53.0	51993	0.0001
0.0009	54.0	52974	0.0040
0.0021	55.0	53955	0.0000
0.0018	56.0	54936	0.0000
0.0005	57.0	55917	0.0000
0.0	58.0	56898	0.0000
0.0014	59.0	57879	0.0000
0.0008	60.0	58860	0.0000
0.0002	61.0	59841	0.0000
0.0018	62.0	60822	0.0000
0.0016	63.0	61803	0.0003
0.0	64.0	62784	0.0000
0.0001	65.0	63765	0.0000
0.0014	66.0	64746	0.0004
0.0006	67.0	65727	0.0000
0.0	68.0	66708	0.0000
0.0	69.0	67689	0.0000
0.0002	70.0	68670	0.0000
0.0001	71.0	69651	0.0000
0.0	72.0	70632	0.0000
0.0005	73.0	71613	0.0000
0.0009	74.0	72594	0.0000
0.0007	75.0	73575	0.0000
0.0	76.0	74556	0.0005
0.0	77.0	75537	0.0000
0.0	78.0	76518	0.0000
0.0004	79.0	77499	0.0000
0.0001	80.0	78480	0.0000
0.0	81.0	79461	0.0000
0.0013	82.0	80442	0.0000
0.0	83.0	81423	0.0000
0.0	84.0	82404	0.0000
0.0	85.0	83385	0.0000
0.0001	86.0	84366	0.0000
0.001	87.0	85347	0.0000
0.0	88.0	86328	0.0000
0.0001	89.0	87309	0.0000
0.0004	90.0	88290	0.0000
0.0	91.0	89271	0.0000
0.0	92.0	90252	0.0000
0.0	93.0	91233	0.0000
0.001	94.0	92214	0.0000
0.0	95.0	93195	0.0000
0.0	96.0	94176	0.0000
0.0	97.0	95157	0.0000
0.0007	98.0	96138	0.0000
0.0	99.0	97119	0.0000
0.0	100.0	98100	0.0000
0.0	101.0	99081	0.0000
0.0	102.0	100062	0.0000
0.0	103.0	101043	0.0
0.0	104.0	102024	0.0000
0.0	105.0	103005	0.0000
0.0	106.0	103986	0.0000
0.0	107.0	104967	0.0
0.0	108.0	105948	0.0000
0.0006	109.0	106929	0.0000
0.0	110.0	107910	0.0000
0.0	111.0	108891	0.0
0.0	112.0	109872	0.0
0.0	113.0	110853	0.0
0.0	114.0	111834	0.0
0.0	115.0	112815	0.0000
0.0	116.0	113796	0.0000
0.0	117.0	114777	0.0000
0.0	118.0	115758	0.0000
0.0	119.0	116739	0.0000
0.0	120.0	117720	0.0
0.0	121.0	118701	0.0
0.0	122.0	119682	0.0
0.0	123.0	120663	0.0
0.0013	124.0	121644	0.0000
0.0	125.0	122625	0.0000
0.0	126.0	123606	0.0000
0.0	127.0	124587	0.0000
0.0	128.0	125568	0.0000
0.0	129.0	126549	0.0000
0.0	130.0	127530	0.0
0.0	131.0	128511	0.0
0.0	132.0	129492	0.0
0.0	133.0	130473	0.0
0.0	134.0	131454	0.0
0.0	135.0	132435	0.0
0.0	136.0	133416	0.0
0.0	137.0	134397	0.0
0.0	138.0	135378	0.0
0.0	139.0	136359	0.0
0.0	140.0	137340	0.0
0.0	141.0	138321	0.0
0.0	142.0	139302	0.0
0.0	143.0	140283	0.0
0.0	144.0	141264	0.0
0.0	145.0	142245	0.0
0.0	146.0	143226	0.0
0.0	147.0	144207	0.0
0.0	148.0	145188	0.0
0.0	149.0	146169	0.0
0.0	150.0	147150	0.0

Framework versions

• Transformers 4.33.2
• Pytorch 2.0.1+cu118
• Tokenizers 0.13.3