Legal_GQA_BERT_augmented_1000

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

• Loss: 5.5643

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1000

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	15	3.3883
No log	2.0	30	3.5183
No log	3.0	45	3.2108
No log	4.0	60	3.1069
No log	5.0	75	3.2101
No log	6.0	90	3.3867
No log	7.0	105	3.6980
No log	8.0	120	3.9139
No log	9.0	135	4.0341
No log	10.0	150	3.8068
No log	11.0	165	4.1122
No log	12.0	180	4.0931
No log	13.0	195	4.4698
No log	14.0	210	4.5345
No log	15.0	225	4.2682
No log	16.0	240	4.2651
No log	17.0	255	4.3404
No log	18.0	270	4.1897
No log	19.0	285	4.2439
No log	20.0	300	4.2961
No log	21.0	315	4.4664
No log	22.0	330	4.6397
No log	23.0	345	4.6983
No log	24.0	360	4.3461
No log	25.0	375	4.3599
No log	26.0	390	4.6474
No log	27.0	405	4.8310
No log	28.0	420	4.7413
No log	29.0	435	4.6552
No log	30.0	450	5.0394
No log	31.0	465	5.1472
No log	32.0	480	4.3219
No log	33.0	495	5.0297
1.0978	34.0	510	4.9553
1.0978	35.0	525	4.5924
1.0978	36.0	540	4.6446
1.0978	37.0	555	4.6058
1.0978	38.0	570	4.6765
1.0978	39.0	585	4.6653
1.0978	40.0	600	4.7802
1.0978	41.0	615	4.8281
1.0978	42.0	630	4.6197
1.0978	43.0	645	5.3967
1.0978	44.0	660	5.1220
1.0978	45.0	675	4.6703
1.0978	46.0	690	4.8150
1.0978	47.0	705	4.8910
1.0978	48.0	720	4.8554
1.0978	49.0	735	4.7086
1.0978	50.0	750	5.3159
1.0978	51.0	765	4.8209
1.0978	52.0	780	4.6739
1.0978	53.0	795	4.8043
1.0978	54.0	810	4.7875
1.0978	55.0	825	5.1071
1.0978	56.0	840	4.9139
1.0978	57.0	855	4.8034
1.0978	58.0	870	5.2768
1.0978	59.0	885	4.5211
1.0978	60.0	900	4.8944
1.0978	61.0	915	5.2514
1.0978	62.0	930	5.0131
1.0978	63.0	945	4.8093
1.0978	64.0	960	5.0798
1.0978	65.0	975	5.0009
1.0978	66.0	990	4.7921
0.545	67.0	1005	4.4796
0.545	68.0	1020	4.6143
0.545	69.0	1035	4.6604
0.545	70.0	1050	4.8758
0.545	71.0	1065	4.6794
0.545	72.0	1080	4.7766
0.545	73.0	1095	4.7499
0.545	74.0	1110	5.0082
0.545	75.0	1125	4.8711
0.545	76.0	1140	5.2020
0.545	77.0	1155	4.7688
0.545	78.0	1170	4.9599
0.545	79.0	1185	4.9073
0.545	80.0	1200	4.7357
0.545	81.0	1215	4.8469
0.545	82.0	1230	4.7376
0.545	83.0	1245	5.2470
0.545	84.0	1260	4.8735
0.545	85.0	1275	5.2453
0.545	86.0	1290	4.9205
0.545	87.0	1305	5.1069
0.545	88.0	1320	5.1398
0.545	89.0	1335	5.3820
0.545	90.0	1350	4.7635
0.545	91.0	1365	5.0217
0.545	92.0	1380	5.2565
0.545	93.0	1395	4.7166
0.545	94.0	1410	4.9733
0.545	95.0	1425	5.0055
0.545	96.0	1440	4.7976
0.545	97.0	1455	5.0151
0.545	98.0	1470	5.2870
0.545	99.0	1485	4.5921
0.5267	100.0	1500	5.0646
0.5267	101.0	1515	4.8235
0.5267	102.0	1530	5.2986
0.5267	103.0	1545	5.4820
0.5267	104.0	1560	4.8970
0.5267	105.0	1575	4.7869
0.5267	106.0	1590	4.8999
0.5267	107.0	1605	5.1031
0.5267	108.0	1620	5.2480
0.5267	109.0	1635	4.9032
0.5267	110.0	1650	4.8363
0.5267	111.0	1665	4.5870
0.5267	112.0	1680	5.1484
0.5267	113.0	1695	5.1142
0.5267	114.0	1710	4.9887
0.5267	115.0	1725	4.8359
0.5267	116.0	1740	5.3862
0.5267	117.0	1755	5.2256
0.5267	118.0	1770	5.2384
0.5267	119.0	1785	5.4806
0.5267	120.0	1800	5.4251
0.5267	121.0	1815	5.0972
0.5267	122.0	1830	5.3176
0.5267	123.0	1845	5.5421
0.5267	124.0	1860	5.3288
0.5267	125.0	1875	5.1236
0.5267	126.0	1890	4.8576
0.5267	127.0	1905	5.2399
0.5267	128.0	1920	5.1789
0.5267	129.0	1935	5.2044
0.5267	130.0	1950	5.0341
0.5267	131.0	1965	5.0332
0.5267	132.0	1980	5.3033
0.5267	133.0	1995	4.9757
0.5255	134.0	2010	4.9756
0.5255	135.0	2025	5.9108
0.5255	136.0	2040	5.1210
0.5255	137.0	2055	5.1198
0.5255	138.0	2070	4.7941
0.5255	139.0	2085	5.1223
0.5255	140.0	2100	5.5357
0.5255	141.0	2115	5.7372
0.5255	142.0	2130	5.1258
0.5255	143.0	2145	4.8953
0.5255	144.0	2160	5.3617
0.5255	145.0	2175	4.7360
0.5255	146.0	2190	5.2179
0.5255	147.0	2205	5.1701
0.5255	148.0	2220	5.1744
0.5255	149.0	2235	5.6116
0.5255	150.0	2250	4.9830
0.5255	151.0	2265	5.1670
0.5255	152.0	2280	5.3134
0.5255	153.0	2295	5.3584
0.5255	154.0	2310	5.1973
0.5255	155.0	2325	5.1849
0.5255	156.0	2340	5.0317
0.5255	157.0	2355	5.2188
0.5255	158.0	2370	5.4852
0.5255	159.0	2385	5.2943
0.5255	160.0	2400	5.0760
0.5255	161.0	2415	5.7740
0.5255	162.0	2430	4.7469
0.5255	163.0	2445	5.2974
0.5255	164.0	2460	5.5422
0.5255	165.0	2475	5.1533
0.5255	166.0	2490	5.5896
0.5186	167.0	2505	5.1866
0.5186	168.0	2520	5.3227
0.5186	169.0	2535	4.9270
0.5186	170.0	2550	4.8544
0.5186	171.0	2565	5.1769
0.5186	172.0	2580	5.4327
0.5186	173.0	2595	4.8254
0.5186	174.0	2610	4.5861
0.5186	175.0	2625	5.5166
0.5186	176.0	2640	5.3005
0.5186	177.0	2655	4.9372
0.5186	178.0	2670	4.7945
0.5186	179.0	2685	5.0823
0.5186	180.0	2700	5.4074
0.5186	181.0	2715	4.9503
0.5186	182.0	2730	4.8464
0.5186	183.0	2745	5.3896
0.5186	184.0	2760	5.3146
0.5186	185.0	2775	5.3931
0.5186	186.0	2790	5.3056
0.5186	187.0	2805	5.0436
0.5186	188.0	2820	4.8892
0.5186	189.0	2835	5.0765
0.5186	190.0	2850	5.3206
0.5186	191.0	2865	5.5881
0.5186	192.0	2880	5.3580
0.5186	193.0	2895	5.1613
0.5186	194.0	2910	5.0169
0.5186	195.0	2925	4.9202
0.5186	196.0	2940	4.6891
0.5186	197.0	2955	5.3409
0.5186	198.0	2970	5.1608
0.5186	199.0	2985	5.2628
0.5085	200.0	3000	5.3308
0.5085	201.0	3015	4.8390
0.5085	202.0	3030	4.7931
0.5085	203.0	3045	5.0549
0.5085	204.0	3060	5.2469
0.5085	205.0	3075	4.6243
0.5085	206.0	3090	5.4795
0.5085	207.0	3105	5.8197
0.5085	208.0	3120	5.6903
0.5085	209.0	3135	5.1707
0.5085	210.0	3150	5.7986
0.5085	211.0	3165	5.9958
0.5085	212.0	3180	5.1017
0.5085	213.0	3195	4.9035
0.5085	214.0	3210	4.9997
0.5085	215.0	3225	5.3660
0.5085	216.0	3240	6.0097
0.5085	217.0	3255	5.3763
0.5085	218.0	3270	5.1007
0.5085	219.0	3285	5.3806
0.5085	220.0	3300	5.3610
0.5085	221.0	3315	4.9994
0.5085	222.0	3330	5.1716
0.5085	223.0	3345	5.2661
0.5085	224.0	3360	5.0085
0.5085	225.0	3375	4.9746
0.5085	226.0	3390	5.3201
0.5085	227.0	3405	4.8567
0.5085	228.0	3420	4.8498
0.5085	229.0	3435	5.5014
0.5085	230.0	3450	5.6112
0.5085	231.0	3465	4.8397
0.5085	232.0	3480	4.9611
0.5085	233.0	3495	5.0043
0.5054	234.0	3510	4.7918
0.5054	235.0	3525	4.8298
0.5054	236.0	3540	4.9825
0.5054	237.0	3555	4.8376
0.5054	238.0	3570	4.8691
0.5054	239.0	3585	4.8771
0.5054	240.0	3600	5.1065
0.5054	241.0	3615	5.0694
0.5054	242.0	3630	4.8808
0.5054	243.0	3645	5.0120
0.5054	244.0	3660	4.9805
0.5054	245.0	3675	5.0633
0.5054	246.0	3690	4.7455
0.5054	247.0	3705	4.9925
0.5054	248.0	3720	4.8557
0.5054	249.0	3735	5.0092
0.5054	250.0	3750	4.8779
0.5054	251.0	3765	4.7464
0.5054	252.0	3780	5.1301
0.5054	253.0	3795	5.7037
0.5054	254.0	3810	5.5409
0.5054	255.0	3825	5.0423
0.5054	256.0	3840	4.8000
0.5054	257.0	3855	4.7885
0.5054	258.0	3870	5.4398
0.5054	259.0	3885	5.7013
0.5054	260.0	3900	5.4537
0.5054	261.0	3915	5.0434
0.5054	262.0	3930	4.7824
0.5054	263.0	3945	5.4242
0.5054	264.0	3960	5.6762
0.5054	265.0	3975	5.3791
0.5054	266.0	3990	5.2896
0.4997	267.0	4005	5.2966
0.4997	268.0	4020	4.9239
0.4997	269.0	4035	5.4293
0.4997	270.0	4050	5.2644
0.4997	271.0	4065	5.3648
0.4997	272.0	4080	5.0977
0.4997	273.0	4095	5.3462
0.4997	274.0	4110	5.2690
0.4997	275.0	4125	4.8537
0.4997	276.0	4140	4.6817
0.4997	277.0	4155	4.6932
0.4997	278.0	4170	4.7846
0.4997	279.0	4185	4.8426
0.4997	280.0	4200	5.0638
0.4997	281.0	4215	5.2071
0.4997	282.0	4230	5.2970
0.4997	283.0	4245	5.2301
0.4997	284.0	4260	5.1739
0.4997	285.0	4275	5.0952
0.4997	286.0	4290	5.2084
0.4997	287.0	4305	5.0338
0.4997	288.0	4320	5.1577
0.4997	289.0	4335	5.3190
0.4997	290.0	4350	5.0964
0.4997	291.0	4365	4.9452
0.4997	292.0	4380	5.0445
0.4997	293.0	4395	5.1708
0.4997	294.0	4410	5.2879
0.4997	295.0	4425	5.2042
0.4997	296.0	4440	5.2364
0.4997	297.0	4455	5.1176
0.4997	298.0	4470	5.1695
0.4997	299.0	4485	5.2149
0.4995	300.0	4500	5.4318
0.4995	301.0	4515	5.2682
0.4995	302.0	4530	5.1241
0.4995	303.0	4545	5.1414
0.4995	304.0	4560	5.2230
0.4995	305.0	4575	5.2342
0.4995	306.0	4590	5.3834
0.4995	307.0	4605	5.2761
0.4995	308.0	4620	5.0929
0.4995	309.0	4635	4.9035
0.4995	310.0	4650	4.9718
0.4995	311.0	4665	5.1214
0.4995	312.0	4680	5.1096
0.4995	313.0	4695	5.0932
0.4995	314.0	4710	5.3398
0.4995	315.0	4725	5.4340
0.4995	316.0	4740	5.2844
0.4995	317.0	4755	4.9831
0.4995	318.0	4770	5.1183
0.4995	319.0	4785	5.2450
0.4995	320.0	4800	5.1224
0.4995	321.0	4815	5.1252
0.4995	322.0	4830	5.2497
0.4995	323.0	4845	5.1165
0.4995	324.0	4860	5.2975
0.4995	325.0	4875	5.3273
0.4995	326.0	4890	5.1436
0.4995	327.0	4905	5.1417
0.4995	328.0	4920	5.2388
0.4995	329.0	4935	5.2375
0.4995	330.0	4950	5.1233
0.4995	331.0	4965	5.0836
0.4995	332.0	4980	5.0346
0.4995	333.0	4995	5.0839
0.4972	334.0	5010	5.1896
0.4972	335.0	5025	5.1835
0.4972	336.0	5040	5.1205
0.4972	337.0	5055	5.0559
0.4972	338.0	5070	5.1710
0.4972	339.0	5085	5.4036
0.4972	340.0	5100	5.5524
0.4972	341.0	5115	5.4580
0.4972	342.0	5130	5.4039
0.4972	343.0	5145	5.4564
0.4972	344.0	5160	5.3702
0.4972	345.0	5175	5.3680
0.4972	346.0	5190	5.0966
0.4972	347.0	5205	4.9537
0.4972	348.0	5220	4.9034
0.4972	349.0	5235	5.1290
0.4972	350.0	5250	5.3774
0.4972	351.0	5265	5.2119
0.4972	352.0	5280	5.1095
0.4972	353.0	5295	5.0610
0.4972	354.0	5310	5.0331
0.4972	355.0	5325	5.2939
0.4972	356.0	5340	5.3007
0.4972	357.0	5355	5.0598
0.4972	358.0	5370	5.3544
0.4972	359.0	5385	5.6056
0.4972	360.0	5400	5.1976
0.4972	361.0	5415	5.0862
0.4972	362.0	5430	5.1594
0.4972	363.0	5445	5.2028
0.4972	364.0	5460	5.3234
0.4972	365.0	5475	5.3384
0.4972	366.0	5490	5.2076
0.4978	367.0	5505	4.8249
0.4978	368.0	5520	4.7105
0.4978	369.0	5535	4.9459
0.4978	370.0	5550	5.1239
0.4978	371.0	5565	4.8861
0.4978	372.0	5580	5.3975
0.4978	373.0	5595	5.2617
0.4978	374.0	5610	5.2747
0.4978	375.0	5625	5.1127
0.4978	376.0	5640	5.1453
0.4978	377.0	5655	5.2388
0.4978	378.0	5670	5.1525
0.4978	379.0	5685	4.9960
0.4978	380.0	5700	5.3183
0.4978	381.0	5715	5.2230
0.4978	382.0	5730	5.1642
0.4978	383.0	5745	5.5691
0.4978	384.0	5760	5.3970
0.4978	385.0	5775	5.0426
0.4978	386.0	5790	5.2227
0.4978	387.0	5805	5.3170
0.4978	388.0	5820	5.3461
0.4978	389.0	5835	4.6755
0.4978	390.0	5850	4.6388
0.4978	391.0	5865	5.0258
0.4978	392.0	5880	5.2619
0.4978	393.0	5895	5.0009
0.4978	394.0	5910	4.8449
0.4978	395.0	5925	5.2422
0.4978	396.0	5940	5.2006
0.4978	397.0	5955	5.0539
0.4978	398.0	5970	5.2006
0.4978	399.0	5985	5.6585
0.4994	400.0	6000	5.1971
0.4994	401.0	6015	5.0745
0.4994	402.0	6030	5.0704
0.4994	403.0	6045	4.9562
0.4994	404.0	6060	4.9561
0.4994	405.0	6075	5.0316
0.4994	406.0	6090	4.9882
0.4994	407.0	6105	4.8941
0.4994	408.0	6120	4.7548
0.4994	409.0	6135	4.6013
0.4994	410.0	6150	4.6536
0.4994	411.0	6165	4.6243
0.4994	412.0	6180	5.0407
0.4994	413.0	6195	4.9459
0.4994	414.0	6210	5.0777
0.4994	415.0	6225	5.0159
0.4994	416.0	6240	5.3117
0.4994	417.0	6255	5.3360
0.4994	418.0	6270	5.0526
0.4994	419.0	6285	4.9438
0.4994	420.0	6300	4.7978
0.4994	421.0	6315	4.8472
0.4994	422.0	6330	4.9426
0.4994	423.0	6345	5.3218
0.4994	424.0	6360	5.7490
0.4994	425.0	6375	5.8859
0.4994	426.0	6390	6.0392
0.4994	427.0	6405	5.2821
0.4994	428.0	6420	5.0280
0.4994	429.0	6435	5.8315
0.4994	430.0	6450	5.1468
0.4994	431.0	6465	5.0407
0.4994	432.0	6480	5.2883
0.4994	433.0	6495	5.2976
0.4967	434.0	6510	5.4974
0.4967	435.0	6525	5.4830
0.4967	436.0	6540	5.1616
0.4967	437.0	6555	4.9301
0.4967	438.0	6570	5.0119
0.4967	439.0	6585	4.7559
0.4967	440.0	6600	5.0418
0.4967	441.0	6615	5.4243
0.4967	442.0	6630	5.5121
0.4967	443.0	6645	5.8842
0.4967	444.0	6660	5.6200
0.4967	445.0	6675	5.5586
0.4967	446.0	6690	5.1609
0.4967	447.0	6705	5.0849
0.4967	448.0	6720	5.0578
0.4967	449.0	6735	5.3793
0.4967	450.0	6750	5.4016
0.4967	451.0	6765	5.3670
0.4967	452.0	6780	5.3160
0.4967	453.0	6795	4.9808
0.4967	454.0	6810	4.8458
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0.0509	902.0	13530	5.7024
0.0509	903.0	13545	5.7265
0.0509	904.0	13560	5.7009
0.0509	905.0	13575	5.6895
0.0509	906.0	13590	5.7018
0.0509	907.0	13605	5.6948
0.0509	908.0	13620	5.6614
0.0509	909.0	13635	5.6015
0.0509	910.0	13650	5.5796
0.0509	911.0	13665	5.5774
0.0509	912.0	13680	5.5800
0.0509	913.0	13695	5.5879
0.0509	914.0	13710	5.5850
0.0509	915.0	13725	5.5700
0.0509	916.0	13740	5.5868
0.0509	917.0	13755	5.6000
0.0509	918.0	13770	5.6165
0.0509	919.0	13785	5.6243
0.0509	920.0	13800	5.6199
0.0509	921.0	13815	5.6209
0.0509	922.0	13830	5.6377
0.0509	923.0	13845	5.6431
0.0509	924.0	13860	5.6544
0.0509	925.0	13875	5.6521
0.0509	926.0	13890	5.6490
0.0509	927.0	13905	5.6535
0.0509	928.0	13920	5.6498
0.0509	929.0	13935	5.6600
0.0509	930.0	13950	5.6613
0.0509	931.0	13965	5.6576
0.0509	932.0	13980	5.6689
0.0509	933.0	13995	5.6842
0.0513	934.0	14010	5.6979
0.0513	935.0	14025	5.6919
0.0513	936.0	14040	5.6860
0.0513	937.0	14055	5.6731
0.0513	938.0	14070	5.6546
0.0513	939.0	14085	5.6584
0.0513	940.0	14100	5.6556
0.0513	941.0	14115	5.6550
0.0513	942.0	14130	5.6741
0.0513	943.0	14145	5.6691
0.0513	944.0	14160	5.6874
0.0513	945.0	14175	5.6866
0.0513	946.0	14190	5.6379
0.0513	947.0	14205	5.6328
0.0513	948.0	14220	5.6071
0.0513	949.0	14235	5.5959
0.0513	950.0	14250	5.5864
0.0513	951.0	14265	5.5705
0.0513	952.0	14280	5.5751
0.0513	953.0	14295	5.5644
0.0513	954.0	14310	5.5499
0.0513	955.0	14325	5.5551
0.0513	956.0	14340	5.5512
0.0513	957.0	14355	5.5578
0.0513	958.0	14370	5.5631
0.0513	959.0	14385	5.5935
0.0513	960.0	14400	5.6059
0.0513	961.0	14415	5.6193
0.0513	962.0	14430	5.6168
0.0513	963.0	14445	5.6170
0.0513	964.0	14460	5.6137
0.0513	965.0	14475	5.6079
0.0513	966.0	14490	5.6128
0.0507	967.0	14505	5.6038
0.0507	968.0	14520	5.5923
0.0507	969.0	14535	5.5871
0.0507	970.0	14550	5.5726
0.0507	971.0	14565	5.5806
0.0507	972.0	14580	5.5893
0.0507	973.0	14595	5.5825
0.0507	974.0	14610	5.5785
0.0507	975.0	14625	5.5792
0.0507	976.0	14640	5.5787
0.0507	977.0	14655	5.5765
0.0507	978.0	14670	5.5588
0.0507	979.0	14685	5.5557
0.0507	980.0	14700	5.5608
0.0507	981.0	14715	5.5670
0.0507	982.0	14730	5.5633
0.0507	983.0	14745	5.5671
0.0507	984.0	14760	5.5658
0.0507	985.0	14775	5.5648
0.0507	986.0	14790	5.5612
0.0507	987.0	14805	5.5620
0.0507	988.0	14820	5.5596
0.0507	989.0	14835	5.5589
0.0507	990.0	14850	5.5617
0.0507	991.0	14865	5.5616
0.0507	992.0	14880	5.5646
0.0507	993.0	14895	5.5653
0.0507	994.0	14910	5.5637
0.0507	995.0	14925	5.5619
0.0507	996.0	14940	5.5629
0.0507	997.0	14955	5.5635
0.0507	998.0	14970	5.5639
0.0507	999.0	14985	5.5643
0.0511	1000.0	15000	5.5643

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.2+cu121
• Datasets 2.14.7
• Tokenizers 0.15.0