CoolFace
Modelpublic

sharoz/gpt2-medium-custom-functions-dataset-python

sourceHugging Facemitupdated 3y agoView on Hugging Face
0likes29downloads
Model Card

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

gpt2-medium-custom-functions-dataset-python

This model is a fine-tuned version of gpt2-medium on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4735

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
  • trainbatchsize: 8
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 10

Training results

Training LossEpochStepValidation Loss
2.66370.0212.1553
2.45650.0522.0239
2.19680.0731.9137
2.23270.0941.8194
2.06720.1251.7425
1.92920.1461.6721
1.82930.1671.6049
1.710.1981.5385
1.85690.2191.4786
1.72080.23101.4236
1.64610.26111.3770
1.61460.28121.3361
1.57990.3131.3006
1.5150.33141.2690
1.44480.35151.2488
1.28710.37161.2254
1.65660.4171.1972
1.48230.42181.1638
1.46550.44191.1379
1.32270.47201.1172
1.41350.49211.0973
1.48350.51221.0784
1.4010.53231.0607
1.32940.56241.0455
1.47810.58251.0302
1.11670.6261.0153
1.38760.63271.0017
1.17080.65280.9911
1.21990.67290.9833
1.23280.7300.9709
1.52620.72310.9599
1.19060.74320.9501
1.1910.77330.9404
1.04220.79340.9291
1.2770.81350.9183
1.15220.84360.9092
1.18410.86370.9006
1.25380.88380.8931
1.13180.91390.8862
1.0120.93400.8807
1.05530.95410.8753
1.05660.98420.8691
1.12351.0430.8638
1.12071.02440.8591
1.08351.05450.8544
1.37311.07460.8505
0.98431.09470.8450
0.92011.12480.8385
1.03921.14490.8340
1.11581.16500.8297
0.85181.19510.8247
0.88711.21520.8185
1.03781.23530.8124
1.11161.26540.8083
1.03641.28550.8043
0.89491.3560.7988
1.0681.33570.7925
0.93191.35580.7859
0.76541.37590.7818
0.88871.4600.7787
1.02941.42610.7748
1.13511.44620.7711
0.9981.47630.7689
1.11061.49640.7679
0.96061.51650.7660
0.92731.53660.7628
0.97251.56670.7595
1.02051.58680.7569
1.01311.6690.7549
0.92031.63700.7530
0.8981.65710.7508
0.8171.67720.7478
0.94391.7730.7447
1.0791.72740.7427
0.98061.74750.7398
1.2611.77760.7369
1.08241.79770.7340
0.95231.81780.7317
0.97341.84790.7300
1.07861.86800.7302
0.86751.88810.7298
0.8511.91820.7279
1.0661.93830.7254
1.1371.95840.7239
1.13871.98850.7224
0.7392.0860.7207
0.88092.02870.7192
1.02532.05880.7178
0.89422.07890.7160
0.84362.09900.7134
0.83562.12910.7115
0.99512.14920.7110
0.76372.16930.7098
0.7222.19940.7087
1.0232.21950.7072
0.70152.23960.7044
0.89492.26970.7017
0.95732.28980.6996
0.89892.3990.6987
0.97382.331000.6983
0.83172.351010.6970
0.97782.371020.6951
0.79192.41030.6924
0.6532.421040.6898
0.91332.441050.6873
0.85212.471060.6841
0.86732.491070.6808
0.87922.511080.6777
0.86352.531090.6747
1.02992.561100.6719
0.75542.581110.6694
0.91952.61120.6671
0.83742.631130.6649
0.88472.651140.6628
0.9382.671150.6615
0.89672.71160.6603
0.82642.721170.6594
0.91952.741180.6591
0.85842.771190.6588
0.80582.791200.6578
1.09782.811210.6560
0.78892.841220.6544
0.78652.861230.6527
0.85532.881240.6507
0.91342.911250.6486
0.79112.931260.6463
0.96752.951270.6439
0.7612.981280.6417
0.63473.01290.6394
0.76083.021300.6368
0.75633.051310.6352
0.80593.071320.6333
0.88253.091330.6320
0.79523.121340.6307
0.92093.141350.6299
0.85563.161360.6295
0.86133.191370.6289
0.79083.211380.6288
0.77283.231390.6285
0.7073.261400.6280
0.83533.281410.6270
0.94823.31420.6265
0.7263.331430.6260
0.75943.351440.6250
0.94033.371450.6237
0.89863.41460.6218
0.73093.421470.6204
0.80113.441480.6197
0.73733.471490.6193
0.61953.491500.6174
0.86683.511510.6154
0.80963.531520.6136
0.93643.561530.6116
0.70813.581540.6105
0.77993.61550.6091
0.78623.631560.6090
0.72213.651570.6097
0.76053.671580.6090
0.74813.71590.6071
0.7763.721600.6045
0.93963.741610.6022
0.71663.771620.6001
0.7093.791630.5985
0.84123.811640.5970
0.76923.841650.5956
0.76213.861660.5942
0.78323.881670.5930
0.74553.911680.5919
0.78883.931690.5913
0.71973.951700.5908
0.79363.981710.5900
0.59764.01720.5890
0.63754.021730.5874
0.73424.051740.5859
0.6444.071750.5845
0.72324.091760.5831
0.77434.121770.5819
0.80154.141780.5808
0.74754.161790.5801
0.70054.191800.5797
0.70324.211810.5795
0.82044.231820.5789
0.76744.261830.5787
0.72194.281840.5781
0.6244.31850.5771
0.74294.331860.5755
0.64454.351870.5730
0.77824.371880.5712
0.78824.41890.5698
0.70054.421900.5687
0.75094.441910.5678
0.67644.471920.5671
0.65294.491930.5667
0.61014.511940.5668
0.82114.531950.5674
0.75294.561960.5667
0.86154.581970.5651
0.80994.61980.5641
0.71454.631990.5635
0.74374.652000.5632
0.8734.672010.5631
0.79374.72020.5620
0.74934.722030.5608
0.76144.742040.5596
0.66424.772050.5585
0.58544.792060.5576
0.64424.812070.5572
0.8594.842080.5562
0.66274.862090.5553
0.80244.882100.5540
0.74434.912110.5526
0.67254.932120.5520
0.7494.952130.5521
0.76874.982140.5521
0.59985.02150.5522
0.75785.022160.5526
0.70745.052170.5536
0.56475.072180.5543
0.74755.092190.5539
0.57765.122200.5523
0.72325.142210.5507
0.64875.162220.5491
0.64465.192230.5477
0.89515.212240.5467
0.77065.232250.5460
0.63515.262260.5453
0.73365.282270.5445
0.63295.32280.5436
0.57955.332290.5430
0.75535.352300.5428
0.69595.372310.5430
0.59455.42320.5427
0.62745.422330.5422
0.70245.442340.5414
0.82235.472350.5402
0.64415.492360.5386
0.7495.512370.5368
0.66545.532380.5357
0.87815.562390.5346
0.71395.582400.5340
0.5875.62410.5339
0.83085.632420.5340
0.56135.652430.5334
0.71085.672440.5330
0.68845.72450.5322
0.69555.722460.5310
0.59895.742470.5301
0.75175.772480.5295
0.67655.792490.5291
0.62235.812500.5285
0.66945.842510.5277
0.62355.862520.5267
0.65915.882530.5259
0.68325.912540.5251
0.73465.932550.5246
0.65745.952560.5242
0.7045.982570.5236
0.72696.02580.5234
0.60976.022590.5231
0.53696.052600.5224
0.70946.072610.5214
0.6086.092620.5207
0.61126.122630.5200
0.64146.142640.5192
0.62546.162650.5186
0.82196.192660.5184
0.65366.212670.5183
0.6016.232680.5184
0.6726.262690.5182
0.66466.282700.5179
0.72286.32710.5179
0.65426.332720.5182
0.60036.352730.5185
0.47996.372740.5195
0.70626.42750.5203
0.75576.422760.5199
0.74196.442770.5189
0.54686.472780.5179
0.61426.492790.5168
0.59536.512800.5161
0.6026.532810.5152
0.61686.562820.5146
0.8156.582830.5141
0.77386.62840.5138
0.646.632850.5136
0.63776.652860.5133
0.72546.672870.5131
0.64166.72880.5128
0.65556.722890.5123
0.68126.742900.5118
0.71166.772910.5113
0.60466.792920.5104
0.73866.812930.5095
0.7336.842940.5088
0.65796.862950.5081
0.54186.882960.5076
0.58536.912970.5071
0.64886.932980.5070
0.57266.952990.5069
0.58216.983000.5068
0.91577.03010.5068
0.67697.023020.5061
0.76327.053030.5049
0.74797.073040.5037
0.56327.093050.5028
0.64937.123060.5015
0.65177.143070.5007
0.69447.163080.5000
0.58627.193090.4996
0.61617.213100.4993
0.63967.233110.4988
0.55067.263120.4985
0.75187.283130.4982
0.74457.33140.4977
0.62287.333150.4974
0.55557.353160.4968
0.74577.373170.4964
0.5797.43180.4961
0.5287.423190.4956
0.52867.443200.4953
0.5917.473210.4952
0.59037.493220.4953
0.61557.513230.4955
0.59077.533240.4954
0.60287.563250.4949
0.58527.583260.4943
0.61567.63270.4934
0.5827.633280.4925
0.60917.653290.4918
0.58777.673300.4912
0.70177.73310.4908
0.64967.723320.4905
0.60897.743330.4903
0.58077.773340.4901
0.55537.793350.4897
0.80587.813360.4894
0.61477.843370.4892
0.62897.863380.4891
0.58837.883390.4891
0.60487.913400.4890
0.64117.933410.4889
0.55757.953420.4887
0.65097.983430.4884
0.7648.03440.4882
0.63648.023450.4880
0.5618.053460.4880
0.59498.073470.4878
0.69048.093480.4874
0.6478.123490.4868
0.63748.143500.4862
0.70488.163510.4859
0.60858.193520.4854
0.52468.213530.4852
0.5318.233540.4849
0.46058.263550.4844
0.61328.283560.4839
0.63788.33570.4835
0.78858.333580.4831
0.60088.353590.4827
0.71188.373600.4823
0.67928.43610.4821
0.63178.423620.4819
0.59428.443630.4817
0.61848.473640.4815
0.59028.493650.4813
0.53538.513660.4812
0.6858.533670.4812
0.52328.563680.4811
0.63938.583690.4812
0.56858.63700.4812
0.62348.633710.4813
0.54568.653720.4810
0.61598.673730.4807
0.65758.73740.4804
0.57698.723750.4803
0.59398.743760.4801
0.57218.773770.4800
0.52838.793780.4797
0.52758.813790.4795
0.59078.843800.4794
0.60588.863810.4792
0.72028.883820.4790
0.68118.913830.4787
0.59798.933840.4785
0.55728.953850.4783
0.58938.983860.4781
0.67969.03870.4779
0.54129.023880.4780
0.54539.053890.4781
0.74759.073900.4782
0.62229.093910.4781
0.51779.123920.4778
0.61829.143930.4775
0.61249.163940.4772
0.64859.193950.4769
0.58529.213960.4765
0.56569.233970.4761
0.61629.263980.4758
0.69659.283990.4755
0.53429.34000.4753
0.7189.334010.4751
0.50899.354020.4750
0.57389.374030.4748
0.56129.44040.4746
0.56289.424050.4744
0.65129.444060.4743
0.67179.474070.4742
0.59379.494080.4741
0.59069.514090.4741
0.5299.534100.4741
0.65549.564110.4741
0.50749.584120.4741
0.69979.64130.4741
0.55739.634140.4741
0.61139.654150.4741
0.51299.674160.4741
0.54289.74170.4740
0.53639.724180.4739
0.58629.744190.4739
0.61199.774200.4738
0.66989.794210.4738
0.59669.814220.4737
0.53099.844230.4737
0.59249.864240.4736
0.61339.884250.4736
0.68699.914260.4736
0.55089.934270.4735
0.68589.954280.4735
0.56819.984290.4735
0.783410.04300.4735

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3