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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: []
@@ -12,7 +14,14 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.6933
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+ - Accuracy: 0.5
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+ - Tp: 0.0
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+ - Tn: 0.5
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+ - Fp: 0.0
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+ - Fn: 0.5
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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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+ | 0.7085 | 0.8 | 20 | 0.6931 | 0.5025 | 0.0322 | 0.4703 | 0.0297 | 0.4678 |
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+ | 0.7141 | 1.6 | 40 | 0.6974 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7097 | 2.4 | 60 | 0.6933 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7024 | 3.2 | 80 | 0.6951 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6995 | 4.0 | 100 | 0.6933 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.7022 | 4.8 | 120 | 0.6933 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7051 | 5.6 | 140 | 0.7098 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.7009 | 6.4 | 160 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7043 | 7.2 | 180 | 0.6984 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.7 | 8.0 | 200 | 0.6936 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6991 | 8.8 | 220 | 0.6933 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6924 | 9.6 | 240 | 0.6957 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7135 | 10.4 | 260 | 0.6943 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6981 | 11.2 | 280 | 0.6935 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6919 | 12.0 | 300 | 0.6981 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6965 | 12.8 | 320 | 0.6952 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.7 | 13.6 | 340 | 0.6951 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7071 | 14.4 | 360 | 0.7213 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6955 | 15.2 | 380 | 0.6933 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6973 | 16.0 | 400 | 0.6934 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6991 | 16.8 | 420 | 0.6951 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6963 | 17.6 | 440 | 0.6945 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6957 | 18.4 | 460 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.698 | 19.2 | 480 | 0.7071 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7014 | 20.0 | 500 | 0.7042 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6976 | 20.8 | 520 | 0.7058 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6976 | 21.6 | 540 | 0.6964 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.694 | 22.4 | 560 | 0.6937 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.693 | 23.2 | 580 | 0.6980 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7156 | 24.0 | 600 | 0.6967 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7003 | 24.8 | 620 | 0.6953 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7047 | 25.6 | 640 | 0.6957 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7012 | 26.4 | 660 | 0.6939 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6993 | 27.2 | 680 | 0.6934 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.7018 | 28.0 | 700 | 0.6942 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6917 | 28.8 | 720 | 0.6939 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7011 | 29.6 | 740 | 0.6933 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.702 | 30.4 | 760 | 0.6932 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6979 | 31.2 | 780 | 0.6941 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6925 | 32.0 | 800 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6944 | 32.8 | 820 | 0.6935 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6969 | 33.6 | 840 | 0.6932 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6975 | 34.4 | 860 | 0.6937 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6947 | 35.2 | 880 | 0.6959 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.7004 | 36.0 | 900 | 0.6971 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6973 | 36.8 | 920 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6974 | 37.6 | 940 | 0.6937 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6975 | 38.4 | 960 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6952 | 39.2 | 980 | 0.6936 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6929 | 40.0 | 1000 | 0.6931 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6939 | 40.8 | 1020 | 0.6933 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6986 | 41.6 | 1040 | 0.6932 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6931 | 42.4 | 1060 | 0.6932 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6954 | 43.2 | 1080 | 0.6934 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6996 | 44.0 | 1100 | 0.6932 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6917 | 44.8 | 1120 | 0.6936 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6966 | 45.6 | 1140 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6917 | 46.4 | 1160 | 0.6937 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6936 | 47.2 | 1180 | 0.6933 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
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+ | 0.6957 | 48.0 | 1200 | 0.6932 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6938 | 48.8 | 1220 | 0.6932 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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+ | 0.6927 | 49.6 | 1240 | 0.6933 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
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  ### Framework versions
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  - Transformers 4.26.1