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xlnet-base-cased_winobias_finetuned

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xlnet
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  license: mit
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: xlnet-base-cased_winobias_finetuned
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  results: []
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  # xlnet-base-cased_winobias_finetuned
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- This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
 
 
 
 
 
 
 
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  ## Model description
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  - lr_scheduler_type: linear
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  - num_epochs: 50
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  ### Framework versions
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  - Transformers 4.26.1
 
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  license: mit
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  tags:
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  - generated_from_trainer
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+ metrics:
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+ - accuracy
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  model-index:
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  - name: xlnet-base-cased_winobias_finetuned
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  results: []
 
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  # xlnet-base-cased_winobias_finetuned
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+ This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6133
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+ - Accuracy: 0.8232
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+ - Tp: 0.4129
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+ - Tn: 0.4104
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+ - Fp: 0.0896
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+ - Fn: 0.0871
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  ## Model description
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  - lr_scheduler_type: linear
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  - num_epochs: 50
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Tp | Tn | Fp | Fn |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|
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+ | 0.7262 | 0.8 | 20 | 0.6972 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7214 | 1.6 | 40 | 0.7030 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7094 | 2.4 | 60 | 0.6976 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7102 | 3.2 | 80 | 0.6932 | 0.4975 | 0.0518 | 0.4457 | 0.0543 | 0.4482 |
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+ | 0.6953 | 4.0 | 100 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7017 | 4.8 | 120 | 0.6931 | 0.5044 | 0.4173 | 0.0871 | 0.4129 | 0.0827 |
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+ | 0.7098 | 5.6 | 140 | 0.6950 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.7075 | 6.4 | 160 | 0.6932 | 0.5 | 0.4811 | 0.0189 | 0.4811 | 0.0189 |
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+ | 0.7138 | 7.2 | 180 | 0.6935 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.7009 | 8.0 | 200 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7007 | 8.8 | 220 | 0.6932 | 0.5006 | 0.4949 | 0.0057 | 0.4943 | 0.0051 |
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+ | 0.6982 | 9.6 | 240 | 0.6929 | 0.5107 | 0.0638 | 0.4470 | 0.0530 | 0.4362 |
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+ | 0.6991 | 10.4 | 260 | 0.6943 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7027 | 11.2 | 280 | 0.6937 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6944 | 12.0 | 300 | 0.6952 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6928 | 12.8 | 320 | 0.6931 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.707 | 13.6 | 340 | 0.6938 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.7059 | 14.4 | 360 | 0.6935 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7034 | 15.2 | 380 | 0.6939 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.7048 | 16.0 | 400 | 0.6935 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6967 | 16.8 | 420 | 0.6929 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.705 | 17.6 | 440 | 0.6924 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.7008 | 18.4 | 460 | 0.6909 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.565 | 19.2 | 480 | 0.5361 | 0.7418 | 0.4779 | 0.2639 | 0.2361 | 0.0221 |
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+ | 0.4145 | 20.0 | 500 | 0.4368 | 0.7336 | 0.4956 | 0.2380 | 0.2620 | 0.0044 |
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+ | 0.3663 | 20.8 | 520 | 0.4434 | 0.7355 | 0.4943 | 0.2412 | 0.2588 | 0.0057 |
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+ | 0.3586 | 21.6 | 540 | 0.5477 | 0.7670 | 0.3491 | 0.4179 | 0.0821 | 0.1509 |
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+ | 0.3668 | 22.4 | 560 | 0.3964 | 0.7765 | 0.4154 | 0.3611 | 0.1389 | 0.0846 |
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+ | 0.3007 | 23.2 | 580 | 0.5550 | 0.7797 | 0.4394 | 0.3403 | 0.1597 | 0.0606 |
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+ | 0.3052 | 24.0 | 600 | 0.4791 | 0.7992 | 0.4186 | 0.3807 | 0.1193 | 0.0814 |
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+ | 0.2277 | 24.8 | 620 | 0.6168 | 0.8144 | 0.4179 | 0.3965 | 0.1035 | 0.0821 |
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+ | 0.1419 | 25.6 | 640 | 1.0091 | 0.8131 | 0.4097 | 0.4034 | 0.0966 | 0.0903 |
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+ | 0.1323 | 26.4 | 660 | 0.6764 | 0.8106 | 0.4097 | 0.4009 | 0.0991 | 0.0903 |
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+ | 0.1191 | 27.2 | 680 | 0.5545 | 0.8125 | 0.4236 | 0.3889 | 0.1111 | 0.0764 |
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+ | 0.0766 | 28.0 | 700 | 0.9580 | 0.8169 | 0.4167 | 0.4003 | 0.0997 | 0.0833 |
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+ | 0.0452 | 28.8 | 720 | 1.1316 | 0.8157 | 0.4009 | 0.4148 | 0.0852 | 0.0991 |
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+ | 0.0491 | 29.6 | 740 | 1.2071 | 0.8119 | 0.4154 | 0.3965 | 0.1035 | 0.0846 |
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+ | 0.073 | 30.4 | 760 | 1.1414 | 0.8163 | 0.3914 | 0.4249 | 0.0751 | 0.1086 |
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+ | 0.0496 | 31.2 | 780 | 1.0776 | 0.8182 | 0.4255 | 0.3927 | 0.1073 | 0.0745 |
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+ | 0.0296 | 32.0 | 800 | 1.1979 | 0.8188 | 0.4078 | 0.4110 | 0.0890 | 0.0922 |
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+ | 0.0379 | 32.8 | 820 | 1.2639 | 0.8201 | 0.4167 | 0.4034 | 0.0966 | 0.0833 |
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+ | 0.0165 | 33.6 | 840 | 1.3292 | 0.8125 | 0.3958 | 0.4167 | 0.0833 | 0.1042 |
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+ | 0.0132 | 34.4 | 860 | 1.4465 | 0.8169 | 0.3971 | 0.4198 | 0.0802 | 0.1029 |
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+ | 0.0205 | 35.2 | 880 | 1.3776 | 0.8201 | 0.4091 | 0.4110 | 0.0890 | 0.0909 |
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+ | 0.0051 | 36.0 | 900 | 1.3503 | 0.8207 | 0.4116 | 0.4091 | 0.0909 | 0.0884 |
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+ | 0.0013 | 36.8 | 920 | 1.4425 | 0.8213 | 0.4072 | 0.4141 | 0.0859 | 0.0928 |
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+ | 0.0002 | 37.6 | 940 | 1.4601 | 0.8226 | 0.4028 | 0.4198 | 0.0802 | 0.0972 |
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+ | 0.0007 | 38.4 | 960 | 1.5047 | 0.8213 | 0.4034 | 0.4179 | 0.0821 | 0.0966 |
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+ | 0.0002 | 39.2 | 980 | 1.5297 | 0.8207 | 0.4072 | 0.4135 | 0.0865 | 0.0928 |
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+ | 0.0002 | 40.0 | 1000 | 1.5409 | 0.8226 | 0.4122 | 0.4104 | 0.0896 | 0.0878 |
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+ | 0.0002 | 40.8 | 1020 | 1.5452 | 0.8239 | 0.4097 | 0.4141 | 0.0859 | 0.0903 |
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+ | 0.0001 | 41.6 | 1040 | 1.6013 | 0.8194 | 0.4097 | 0.4097 | 0.0903 | 0.0903 |
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+ | 0.0001 | 42.4 | 1060 | 1.6177 | 0.8201 | 0.4104 | 0.4097 | 0.0903 | 0.0896 |
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+ | 0.0001 | 43.2 | 1080 | 1.6290 | 0.8201 | 0.4104 | 0.4097 | 0.0903 | 0.0896 |
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+ | 0.0001 | 44.0 | 1100 | 1.6365 | 0.8201 | 0.4097 | 0.4104 | 0.0896 | 0.0903 |
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+ | 0.0001 | 44.8 | 1120 | 1.6425 | 0.8194 | 0.4097 | 0.4097 | 0.0903 | 0.0903 |
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+ | 0.0142 | 45.6 | 1140 | 1.6429 | 0.8220 | 0.4110 | 0.4110 | 0.0890 | 0.0890 |
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+ | 0.0001 | 46.4 | 1160 | 1.6080 | 0.8239 | 0.4135 | 0.4104 | 0.0896 | 0.0865 |
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+ | 0.0001 | 47.2 | 1180 | 1.6113 | 0.8239 | 0.4135 | 0.4104 | 0.0896 | 0.0865 |
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+ | 0.0001 | 48.0 | 1200 | 1.6046 | 0.8239 | 0.4129 | 0.4110 | 0.0890 | 0.0871 |
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+ | 0.0001 | 48.8 | 1220 | 1.6066 | 0.8239 | 0.4135 | 0.4104 | 0.0896 | 0.0865 |
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+ | 0.0001 | 49.6 | 1240 | 1.6133 | 0.8232 | 0.4129 | 0.4104 | 0.0896 | 0.0871 |
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+
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+
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  ### Framework versions
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  - Transformers 4.26.1