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Bloom-Medical-QA-LoRA

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metadata
base_model: bigscience/bloom-560m
library_name: peft
license: bigscience-bloom-rail-1.0
tags:
  - generated_from_trainer
model-index:
  - name: Bloom-Medical-QA-LoRA
    results: []

Bloom-Medical-QA-LoRA

This model is a fine-tuned version of bigscience/bloom-560m on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.9628

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: 0.0001
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss
No log 0.0084 10 2.7413
No log 0.0168 20 2.5065
No log 0.0253 30 2.3701
No log 0.0337 40 2.3103
No log 0.0421 50 2.2831
No log 0.0505 60 2.2652
No log 0.0589 70 2.2498
No log 0.0673 80 2.2374
No log 0.0758 90 2.2281
2.3686 0.0842 100 2.2183
2.3686 0.0926 110 2.2133
2.3686 0.1010 120 2.2091
2.3686 0.1094 130 2.2030
2.3686 0.1178 140 2.1965
2.3686 0.1263 150 2.1939
2.3686 0.1347 160 2.1885
2.3686 0.1431 170 2.1814
2.3686 0.1515 180 2.1808
2.3686 0.1599 190 2.1746
2.1271 0.1684 200 2.1743
2.1271 0.1768 210 2.1719
2.1271 0.1852 220 2.1679
2.1271 0.1936 230 2.1720
2.1271 0.2020 240 2.1648
2.1271 0.2104 250 2.1624
2.1271 0.2189 260 2.1563
2.1271 0.2273 270 2.1489
2.1271 0.2357 280 2.1451
2.1271 0.2441 290 2.1420
2.0973 0.2525 300 2.1438
2.0973 0.2609 310 2.1409
2.0973 0.2694 320 2.1397
2.0973 0.2778 330 2.1371
2.0973 0.2862 340 2.1320
2.0973 0.2946 350 2.1353
2.0973 0.3030 360 2.1321
2.0973 0.3114 370 2.1279
2.0973 0.3199 380 2.1283
2.0973 0.3283 390 2.1244
2.1201 0.3367 400 2.1242
2.1201 0.3451 410 2.1205
2.1201 0.3535 420 2.1179
2.1201 0.3620 430 2.1162
2.1201 0.3704 440 2.1129
2.1201 0.3788 450 2.1123
2.1201 0.3872 460 2.1120
2.1201 0.3956 470 2.1114
2.1201 0.4040 480 2.1121
2.1201 0.4125 490 2.1089
2.0368 0.4209 500 2.1085
2.0368 0.4293 510 2.1065
2.0368 0.4377 520 2.1041
2.0368 0.4461 530 2.1016
2.0368 0.4545 540 2.1042
2.0368 0.4630 550 2.0996
2.0368 0.4714 560 2.1002
2.0368 0.4798 570 2.0997
2.0368 0.4882 580 2.0959
2.0368 0.4966 590 2.0952
2.0816 0.5051 600 2.0964
2.0816 0.5135 610 2.0969
2.0816 0.5219 620 2.0963
2.0816 0.5303 630 2.0928
2.0816 0.5387 640 2.0892
2.0816 0.5471 650 2.0889
2.0816 0.5556 660 2.0860
2.0816 0.5640 670 2.0873
2.0816 0.5724 680 2.0827
2.0816 0.5808 690 2.0814
2.0766 0.5892 700 2.0824
2.0766 0.5976 710 2.0810
2.0766 0.6061 720 2.0802
2.0766 0.6145 730 2.0800
2.0766 0.6229 740 2.0790
2.0766 0.6313 750 2.0811
2.0766 0.6397 760 2.0810
2.0766 0.6481 770 2.0778
2.0766 0.6566 780 2.0770
2.0766 0.6650 790 2.0753
2.0604 0.6734 800 2.0752
2.0604 0.6818 810 2.0719
2.0604 0.6902 820 2.0759
2.0604 0.6987 830 2.0743
2.0604 0.7071 840 2.0682
2.0604 0.7155 850 2.0686
2.0604 0.7239 860 2.0661
2.0604 0.7323 870 2.0669
2.0604 0.7407 880 2.0670
2.0604 0.7492 890 2.0694
2.0319 0.7576 900 2.0645
2.0319 0.7660 910 2.0633
2.0319 0.7744 920 2.0592
2.0319 0.7828 930 2.0618
2.0319 0.7912 940 2.0613
2.0319 0.7997 950 2.0620
2.0319 0.8081 960 2.0589
2.0319 0.8165 970 2.0599
2.0319 0.8249 980 2.0576
2.0319 0.8333 990 2.0564
2.0554 0.8418 1000 2.0555
2.0554 0.8502 1010 2.0574
2.0554 0.8586 1020 2.0555
2.0554 0.8670 1030 2.0531
2.0554 0.8754 1040 2.0546
2.0554 0.8838 1050 2.0533
2.0554 0.8923 1060 2.0526
2.0554 0.9007 1070 2.0515
2.0554 0.9091 1080 2.0492
2.0554 0.9175 1090 2.0490
2.0078 0.9259 1100 2.0514
2.0078 0.9343 1110 2.0493
2.0078 0.9428 1120 2.0454
2.0078 0.9512 1130 2.0472
2.0078 0.9596 1140 2.0481
2.0078 0.9680 1150 2.0448
2.0078 0.9764 1160 2.0423
2.0078 0.9848 1170 2.0424
2.0078 0.9933 1180 2.0413
2.0078 1.0017 1190 2.0376
2.0269 1.0101 1200 2.0380
2.0269 1.0185 1210 2.0383
2.0269 1.0269 1220 2.0385
2.0269 1.0354 1230 2.0381
2.0269 1.0438 1240 2.0416
2.0269 1.0522 1250 2.0406
2.0269 1.0606 1260 2.0399
2.0269 1.0690 1270 2.0407
2.0269 1.0774 1280 2.0414
2.0269 1.0859 1290 2.0404
1.9814 1.0943 1300 2.0383
1.9814 1.1027 1310 2.0376
1.9814 1.1111 1320 2.0361
1.9814 1.1195 1330 2.0326
1.9814 1.1279 1340 2.0351
1.9814 1.1364 1350 2.0322
1.9814 1.1448 1360 2.0285
1.9814 1.1532 1370 2.0276
1.9814 1.1616 1380 2.0278
1.9814 1.1700 1390 2.0309
1.9846 1.1785 1400 2.0319
1.9846 1.1869 1410 2.0311
1.9846 1.1953 1420 2.0321
1.9846 1.2037 1430 2.0322
1.9846 1.2121 1440 2.0368
1.9846 1.2205 1450 2.0330
1.9846 1.2290 1460 2.0270
1.9846 1.2374 1470 2.0256
1.9846 1.2458 1480 2.0243
1.9846 1.2542 1490 2.0239
1.9862 1.2626 1500 2.0211
1.9862 1.2710 1510 2.0203
1.9862 1.2795 1520 2.0216
1.9862 1.2879 1530 2.0205
1.9862 1.2963 1540 2.0214
1.9862 1.3047 1550 2.0214
1.9862 1.3131 1560 2.0171
1.9862 1.3215 1570 2.0198
1.9862 1.3300 1580 2.0220
1.9862 1.3384 1590 2.0202
1.9507 1.3468 1600 2.0211
1.9507 1.3552 1610 2.0191
1.9507 1.3636 1620 2.0187
1.9507 1.3721 1630 2.0187
1.9507 1.3805 1640 2.0165
1.9507 1.3889 1650 2.0185
1.9507 1.3973 1660 2.0192
1.9507 1.4057 1670 2.0160
1.9507 1.4141 1680 2.0153
1.9507 1.4226 1690 2.0163
1.9746 1.4310 1700 2.0180
1.9746 1.4394 1710 2.0172
1.9746 1.4478 1720 2.0176
1.9746 1.4562 1730 2.0176
1.9746 1.4646 1740 2.0181
1.9746 1.4731 1750 2.0217
1.9746 1.4815 1760 2.0169
1.9746 1.4899 1770 2.0165
1.9746 1.4983 1780 2.0155
1.9746 1.5067 1790 2.0160
1.9464 1.5152 1800 2.0110
1.9464 1.5236 1810 2.0142
1.9464 1.5320 1820 2.0143
1.9464 1.5404 1830 2.0145
1.9464 1.5488 1840 2.0121
1.9464 1.5572 1850 2.0115
1.9464 1.5657 1860 2.0114
1.9464 1.5741 1870 2.0107
1.9464 1.5825 1880 2.0143
1.9464 1.5909 1890 2.0151
1.9539 1.5993 1900 2.0120
1.9539 1.6077 1910 2.0087
1.9539 1.6162 1920 2.0083
1.9539 1.6246 1930 2.0092
1.9539 1.6330 1940 2.0126
1.9539 1.6414 1950 2.0111
1.9539 1.6498 1960 2.0081
1.9539 1.6582 1970 2.0076
1.9539 1.6667 1980 2.0076
1.9539 1.6751 1990 2.0081
1.9227 1.6835 2000 2.0064
1.9227 1.6919 2010 2.0079
1.9227 1.7003 2020 2.0054
1.9227 1.7088 2030 2.0047
1.9227 1.7172 2040 2.0066
1.9227 1.7256 2050 2.0059
1.9227 1.7340 2060 2.0048
1.9227 1.7424 2070 2.0054
1.9227 1.7508 2080 2.0052
1.9227 1.7593 2090 2.0062
1.9588 1.7677 2100 2.0074
1.9588 1.7761 2110 2.0065
1.9588 1.7845 2120 2.0022
1.9588 1.7929 2130 2.0014
1.9588 1.8013 2140 1.9998
1.9588 1.8098 2150 2.0009
1.9588 1.8182 2160 2.0026
1.9588 1.8266 2170 2.0038
1.9588 1.8350 2180 2.0019
1.9588 1.8434 2190 2.0002
1.9351 1.8519 2200 2.0010
1.9351 1.8603 2210 2.0016
1.9351 1.8687 2220 2.0031
1.9351 1.8771 2230 1.9999
1.9351 1.8855 2240 1.9981
1.9351 1.8939 2250 1.9963
1.9351 1.9024 2260 1.9965
1.9351 1.9108 2270 1.9990
1.9351 1.9192 2280 1.9989
1.9351 1.9276 2290 1.9954
1.9219 1.9360 2300 1.9965
1.9219 1.9444 2310 1.9982
1.9219 1.9529 2320 1.9991
1.9219 1.9613 2330 1.9970
1.9219 1.9697 2340 1.9957
1.9219 1.9781 2350 1.9954
1.9219 1.9865 2360 1.9947
1.9219 1.9949 2370 1.9948
1.9219 2.0034 2380 1.9933
1.9219 2.0118 2390 1.9943
1.9129 2.0202 2400 1.9956
1.9129 2.0286 2410 1.9949
1.9129 2.0370 2420 1.9961
1.9129 2.0455 2430 1.9950
1.9129 2.0539 2440 1.9956
1.9129 2.0623 2450 1.9950
1.9129 2.0707 2460 1.9941
1.9129 2.0791 2470 1.9946
1.9129 2.0875 2480 1.9928
1.9129 2.0960 2490 1.9951
1.8814 2.1044 2500 1.9968
1.8814 2.1128 2510 1.9928
1.8814 2.1212 2520 1.9948
1.8814 2.1296 2530 1.9925
1.8814 2.1380 2540 1.9923
1.8814 2.1465 2550 1.9924
1.8814 2.1549 2560 1.9915
1.8814 2.1633 2570 1.9918
1.8814 2.1717 2580 1.9913
1.8814 2.1801 2590 1.9900
1.914 2.1886 2600 1.9894
1.914 2.1970 2610 1.9902
1.914 2.2054 2620 1.9896
1.914 2.2138 2630 1.9896
1.914 2.2222 2640 1.9889
1.914 2.2306 2650 1.9887
1.914 2.2391 2660 1.9884
1.914 2.2475 2670 1.9877
1.914 2.2559 2680 1.9882
1.914 2.2643 2690 1.9887
1.8883 2.2727 2700 1.9896
1.8883 2.2811 2710 1.9909
1.8883 2.2896 2720 1.9905
1.8883 2.2980 2730 1.9902
1.8883 2.3064 2740 1.9886
1.8883 2.3148 2750 1.9888
1.8883 2.3232 2760 1.9889
1.8883 2.3316 2770 1.9905
1.8883 2.3401 2780 1.9899
1.8883 2.3485 2790 1.9896
1.8748 2.3569 2800 1.9878
1.8748 2.3653 2810 1.9873
1.8748 2.3737 2820 1.9861
1.8748 2.3822 2830 1.9873
1.8748 2.3906 2840 1.9847
1.8748 2.3990 2850 1.9827
1.8748 2.4074 2860 1.9823
1.8748 2.4158 2870 1.9822
1.8748 2.4242 2880 1.9851
1.8748 2.4327 2890 1.9857
1.9119 2.4411 2900 1.9847
1.9119 2.4495 2910 1.9828
1.9119 2.4579 2920 1.9824
1.9119 2.4663 2930 1.9828
1.9119 2.4747 2940 1.9839
1.9119 2.4832 2950 1.9829
1.9119 2.4916 2960 1.9815
1.9119 2.5 2970 1.9804
1.9119 2.5084 2980 1.9832
1.9119 2.5168 2990 1.9858
1.8855 2.5253 3000 1.9858
1.8855 2.5337 3010 1.9844
1.8855 2.5421 3020 1.9842
1.8855 2.5505 3030 1.9811
1.8855 2.5589 3040 1.9796
1.8855 2.5673 3050 1.9804
1.8855 2.5758 3060 1.9821
1.8855 2.5842 3070 1.9805
1.8855 2.5926 3080 1.9784
1.8855 2.6010 3090 1.9787
1.88 2.6094 3100 1.9784
1.88 2.6178 3110 1.9776
1.88 2.6263 3120 1.9782
1.88 2.6347 3130 1.9764
1.88 2.6431 3140 1.9749
1.88 2.6515 3150 1.9749
1.88 2.6599 3160 1.9759
1.88 2.6684 3170 1.9768
1.88 2.6768 3180 1.9778
1.88 2.6852 3190 1.9770
1.8669 2.6936 3200 1.9770
1.8669 2.7020 3210 1.9749
1.8669 2.7104 3220 1.9738
1.8669 2.7189 3230 1.9748
1.8669 2.7273 3240 1.9749
1.8669 2.7357 3250 1.9764
1.8669 2.7441 3260 1.9756
1.8669 2.7525 3270 1.9755
1.8669 2.7609 3280 1.9746
1.8669 2.7694 3290 1.9747
1.8636 2.7778 3300 1.9758
1.8636 2.7862 3310 1.9753
1.8636 2.7946 3320 1.9735
1.8636 2.8030 3330 1.9733
1.8636 2.8114 3340 1.9746
1.8636 2.8199 3350 1.9753
1.8636 2.8283 3360 1.9764
1.8636 2.8367 3370 1.9764
1.8636 2.8451 3380 1.9755
1.8636 2.8535 3390 1.9751
1.8587 2.8620 3400 1.9753
1.8587 2.8704 3410 1.9759
1.8587 2.8788 3420 1.9764
1.8587 2.8872 3430 1.9747
1.8587 2.8956 3440 1.9730
1.8587 2.9040 3450 1.9731
1.8587 2.9125 3460 1.9719
1.8587 2.9209 3470 1.9703
1.8587 2.9293 3480 1.9704
1.8587 2.9377 3490 1.9699
1.8189 2.9461 3500 1.9705
1.8189 2.9545 3510 1.9724
1.8189 2.9630 3520 1.9729
1.8189 2.9714 3530 1.9728
1.8189 2.9798 3540 1.9725
1.8189 2.9882 3550 1.9709
1.8189 2.9966 3560 1.9705
1.8189 3.0051 3570 1.9715
1.8189 3.0135 3580 1.9727
1.8189 3.0219 3590 1.9723
1.8332 3.0303 3600 1.9728
1.8332 3.0387 3610 1.9732
1.8332 3.0471 3620 1.9738
1.8332 3.0556 3630 1.9734
1.8332 3.0640 3640 1.9729
1.8332 3.0724 3650 1.9734
1.8332 3.0808 3660 1.9726
1.8332 3.0892 3670 1.9729
1.8332 3.0976 3680 1.9743
1.8332 3.1061 3690 1.9754
1.8035 3.1145 3700 1.9744
1.8035 3.1229 3710 1.9741
1.8035 3.1313 3720 1.9749
1.8035 3.1397 3730 1.9757
1.8035 3.1481 3740 1.9760
1.8035 3.1566 3750 1.9760
1.8035 3.1650 3760 1.9751
1.8035 3.1734 3770 1.9743
1.8035 3.1818 3780 1.9737
1.8035 3.1902 3790 1.9725
1.8222 3.1987 3800 1.9716
1.8222 3.2071 3810 1.9708
1.8222 3.2155 3820 1.9705
1.8222 3.2239 3830 1.9713
1.8222 3.2323 3840 1.9720
1.8222 3.2407 3850 1.9713
1.8222 3.2492 3860 1.9712
1.8222 3.2576 3870 1.9732
1.8222 3.2660 3880 1.9726
1.8222 3.2744 3890 1.9725
1.8209 3.2828 3900 1.9724
1.8209 3.2912 3910 1.9723
1.8209 3.2997 3920 1.9719
1.8209 3.3081 3930 1.9710
1.8209 3.3165 3940 1.9706
1.8209 3.3249 3950 1.9711
1.8209 3.3333 3960 1.9718
1.8209 3.3418 3970 1.9724
1.8209 3.3502 3980 1.9722
1.8209 3.3586 3990 1.9712
1.8311 3.3670 4000 1.9710
1.8311 3.3754 4010 1.9704
1.8311 3.3838 4020 1.9711
1.8311 3.3923 4030 1.9710
1.8311 3.4007 4040 1.9698
1.8311 3.4091 4050 1.9689
1.8311 3.4175 4060 1.9683
1.8311 3.4259 4070 1.9683
1.8311 3.4343 4080 1.9693
1.8311 3.4428 4090 1.9696
1.8518 3.4512 4100 1.9695
1.8518 3.4596 4110 1.9687
1.8518 3.4680 4120 1.9690
1.8518 3.4764 4130 1.9701
1.8518 3.4848 4140 1.9699
1.8518 3.4933 4150 1.9696
1.8518 3.5017 4160 1.9685
1.8518 3.5101 4170 1.9682
1.8518 3.5185 4180 1.9684
1.8518 3.5269 4190 1.9695
1.8257 3.5354 4200 1.9695
1.8257 3.5438 4210 1.9683
1.8257 3.5522 4220 1.9676
1.8257 3.5606 4230 1.9678
1.8257 3.5690 4240 1.9672
1.8257 3.5774 4250 1.9660
1.8257 3.5859 4260 1.9656
1.8257 3.5943 4270 1.9662
1.8257 3.6027 4280 1.9664
1.8257 3.6111 4290 1.9668
1.8107 3.6195 4300 1.9665
1.8107 3.6279 4310 1.9661
1.8107 3.6364 4320 1.9659
1.8107 3.6448 4330 1.9653
1.8107 3.6532 4340 1.9654
1.8107 3.6616 4350 1.9662
1.8107 3.6700 4360 1.9665
1.8107 3.6785 4370 1.9660
1.8107 3.6869 4380 1.9660
1.8107 3.6953 4390 1.9661
1.7929 3.7037 4400 1.9655
1.7929 3.7121 4410 1.9646
1.7929 3.7205 4420 1.9638
1.7929 3.7290 4430 1.9635
1.7929 3.7374 4440 1.9631
1.7929 3.7458 4450 1.9626
1.7929 3.7542 4460 1.9621
1.7929 3.7626 4470 1.9621
1.7929 3.7710 4480 1.9625
1.7929 3.7795 4490 1.9627
1.8177 3.7879 4500 1.9631
1.8177 3.7963 4510 1.9627
1.8177 3.8047 4520 1.9618
1.8177 3.8131 4530 1.9615
1.8177 3.8215 4540 1.9616
1.8177 3.8300 4550 1.9618
1.8177 3.8384 4560 1.9625
1.8177 3.8468 4570 1.9626
1.8177 3.8552 4580 1.9632
1.8177 3.8636 4590 1.9636
1.7996 3.8721 4600 1.9640
1.7996 3.8805 4610 1.9637
1.7996 3.8889 4620 1.9635
1.7996 3.8973 4630 1.9633
1.7996 3.9057 4640 1.9634
1.7996 3.9141 4650 1.9633
1.7996 3.9226 4660 1.9632
1.7996 3.9310 4670 1.9632
1.7996 3.9394 4680 1.9629
1.7996 3.9478 4690 1.9628
1.8443 3.9562 4700 1.9628
1.8443 3.9646 4710 1.9623
1.8443 3.9731 4720 1.9624
1.8443 3.9815 4730 1.9622
1.8443 3.9899 4740 1.9619
1.8443 3.9983 4750 1.9617
1.8443 4.0067 4760 1.9620
1.8443 4.0152 4770 1.9623
1.8443 4.0236 4780 1.9626
1.8443 4.0320 4790 1.9632
1.8409 4.0404 4800 1.9635
1.8409 4.0488 4810 1.9641
1.8409 4.0572 4820 1.9639
1.8409 4.0657 4830 1.9636
1.8409 4.0741 4840 1.9636
1.8409 4.0825 4850 1.9636
1.8409 4.0909 4860 1.9635
1.8409 4.0993 4870 1.9629
1.8409 4.1077 4880 1.9625
1.8409 4.1162 4890 1.9624
1.8261 4.1246 4900 1.9623
1.8261 4.1330 4910 1.9626
1.8261 4.1414 4920 1.9632
1.8261 4.1498 4930 1.9639
1.8261 4.1582 4940 1.9643
1.8261 4.1667 4950 1.9646
1.8261 4.1751 4960 1.9645
1.8261 4.1835 4970 1.9642
1.8261 4.1919 4980 1.9641
1.8261 4.2003 4990 1.9642
1.7684 4.2088 5000 1.9641
1.7684 4.2172 5010 1.9641
1.7684 4.2256 5020 1.9639
1.7684 4.2340 5030 1.9637
1.7684 4.2424 5040 1.9633
1.7684 4.2508 5050 1.9630
1.7684 4.2593 5060 1.9630
1.7684 4.2677 5070 1.9629
1.7684 4.2761 5080 1.9629
1.7684 4.2845 5090 1.9632
1.7933 4.2929 5100 1.9633
1.7933 4.3013 5110 1.9637
1.7933 4.3098 5120 1.9638
1.7933 4.3182 5130 1.9639
1.7933 4.3266 5140 1.9639
1.7933 4.3350 5150 1.9636
1.7933 4.3434 5160 1.9633
1.7933 4.3519 5170 1.9630
1.7933 4.3603 5180 1.9630
1.7933 4.3687 5190 1.9628
1.8192 4.3771 5200 1.9628
1.8192 4.3855 5210 1.9628
1.8192 4.3939 5220 1.9629
1.8192 4.4024 5230 1.9630
1.8192 4.4108 5240 1.9631
1.8192 4.4192 5250 1.9633
1.8192 4.4276 5260 1.9635
1.8192 4.4360 5270 1.9637
1.8192 4.4444 5280 1.9636
1.8192 4.4529 5290 1.9636
1.7583 4.4613 5300 1.9637
1.7583 4.4697 5310 1.9637
1.7583 4.4781 5320 1.9637
1.7583 4.4865 5330 1.9637
1.7583 4.4949 5340 1.9637
1.7583 4.5034 5350 1.9637
1.7583 4.5118 5360 1.9638
1.7583 4.5202 5370 1.9640
1.7583 4.5286 5380 1.9640
1.7583 4.5370 5390 1.9638
1.7977 4.5455 5400 1.9637
1.7977 4.5539 5410 1.9635
1.7977 4.5623 5420 1.9635
1.7977 4.5707 5430 1.9634
1.7977 4.5791 5440 1.9633
1.7977 4.5875 5450 1.9633
1.7977 4.5960 5460 1.9633
1.7977 4.6044 5470 1.9633
1.7977 4.6128 5480 1.9632
1.7977 4.6212 5490 1.9633
1.803 4.6296 5500 1.9633
1.803 4.6380 5510 1.9632
1.803 4.6465 5520 1.9632
1.803 4.6549 5530 1.9632
1.803 4.6633 5540 1.9631
1.803 4.6717 5550 1.9631
1.803 4.6801 5560 1.9630
1.803 4.6886 5570 1.9631
1.803 4.6970 5580 1.9630
1.803 4.7054 5590 1.9630
1.7817 4.7138 5600 1.9630
1.7817 4.7222 5610 1.9629
1.7817 4.7306 5620 1.9629
1.7817 4.7391 5630 1.9628
1.7817 4.7475 5640 1.9629
1.7817 4.7559 5650 1.9629
1.7817 4.7643 5660 1.9629
1.7817 4.7727 5670 1.9629
1.7817 4.7811 5680 1.9629
1.7817 4.7896 5690 1.9629
1.808 4.7980 5700 1.9629
1.808 4.8064 5710 1.9629
1.808 4.8148 5720 1.9629
1.808 4.8232 5730 1.9629
1.808 4.8316 5740 1.9629
1.808 4.8401 5750 1.9628
1.808 4.8485 5760 1.9628
1.808 4.8569 5770 1.9628
1.808 4.8653 5780 1.9628
1.808 4.8737 5790 1.9628
1.8047 4.8822 5800 1.9628
1.8047 4.8906 5810 1.9628
1.8047 4.8990 5820 1.9628
1.8047 4.9074 5830 1.9628
1.8047 4.9158 5840 1.9628
1.8047 4.9242 5850 1.9628
1.8047 4.9327 5860 1.9628
1.8047 4.9411 5870 1.9628
1.8047 4.9495 5880 1.9628
1.8047 4.9579 5890 1.9628
1.7728 4.9663 5900 1.9628
1.7728 4.9747 5910 1.9628
1.7728 4.9832 5920 1.9628
1.7728 4.9916 5930 1.9628
1.7728 5.0 5940 1.9628

Framework versions

  • PEFT 0.11.1
  • Transformers 4.42.4
  • Pytorch 1.13.1+cu117
  • Datasets 2.19.2
  • Tokenizers 0.19.1