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bert-large-uncased_crows_pairs_finetuned

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update model card README.md

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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.46688741721854304
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the crows_pairs dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6936
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- - Accuracy: 0.4669
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  ## Model description
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@@ -51,7 +51,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0005
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  - train_batch_size: 64
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  - eval_batch_size: 64
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  - seed: 42
@@ -63,63 +63,63 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.8146 | 0.53 | 10 | 0.6914 | 0.5331 |
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- | 0.7104 | 1.05 | 20 | 0.6910 | 0.5331 |
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- | 0.7078 | 1.58 | 30 | 0.7292 | 0.4669 |
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- | 0.716 | 2.11 | 40 | 0.7033 | 0.4669 |
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- | 0.7273 | 2.63 | 50 | 0.6946 | 0.5331 |
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- | 0.7285 | 3.16 | 60 | 0.6983 | 0.5331 |
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- | 0.7244 | 3.68 | 70 | 0.6958 | 0.5331 |
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- | 0.7283 | 4.21 | 80 | 0.7013 | 0.4669 |
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- | 0.7131 | 4.74 | 90 | 0.7063 | 0.4669 |
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- | 0.7144 | 5.26 | 100 | 0.7149 | 0.4669 |
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- | 0.7237 | 5.79 | 110 | 0.6913 | 0.5331 |
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- | 0.7074 | 6.32 | 120 | 0.6922 | 0.5331 |
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- | 0.7034 | 6.84 | 130 | 0.6910 | 0.5331 |
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- | 0.699 | 7.37 | 140 | 0.7251 | 0.4669 |
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- | 0.7183 | 7.89 | 150 | 0.7216 | 0.5331 |
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- | 0.7106 | 8.42 | 160 | 0.7046 | 0.4669 |
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- | 0.7107 | 8.95 | 170 | 0.6923 | 0.5331 |
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- | 0.6963 | 9.47 | 180 | 0.7056 | 0.4669 |
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- | 0.7068 | 10.0 | 190 | 0.6911 | 0.5331 |
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- | 0.7088 | 10.53 | 200 | 0.6963 | 0.4669 |
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- | 0.7074 | 11.05 | 210 | 0.7269 | 0.4669 |
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- | 0.7233 | 11.58 | 220 | 0.6995 | 0.5331 |
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- | 0.7261 | 12.11 | 230 | 0.6921 | 0.5331 |
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- | 0.6997 | 12.63 | 240 | 0.6971 | 0.4669 |
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- | 0.6993 | 13.16 | 250 | 0.7103 | 0.4669 |
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- | 0.7073 | 13.68 | 260 | 0.6923 | 0.5331 |
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- | 0.697 | 14.21 | 270 | 0.6938 | 0.4669 |
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- | 0.7057 | 14.74 | 280 | 0.6948 | 0.5331 |
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- | 0.7165 | 15.26 | 290 | 0.7053 | 0.4669 |
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- | 0.7172 | 15.79 | 300 | 0.6910 | 0.5331 |
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- | 0.7152 | 16.32 | 310 | 0.6921 | 0.5331 |
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- | 0.7115 | 16.84 | 320 | 0.7050 | 0.4669 |
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- | 0.7202 | 17.37 | 330 | 0.6911 | 0.5331 |
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- | 0.7069 | 17.89 | 340 | 0.6952 | 0.4669 |
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- | 0.7061 | 18.42 | 350 | 0.6914 | 0.5331 |
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- | 0.7023 | 18.95 | 360 | 0.6943 | 0.4669 |
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- | 0.7045 | 19.47 | 370 | 0.6911 | 0.5331 |
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- | 0.7114 | 20.0 | 380 | 0.6925 | 0.5331 |
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- | 0.6922 | 20.53 | 390 | 0.6910 | 0.5331 |
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- | 0.7097 | 21.05 | 400 | 0.6919 | 0.5331 |
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- | 0.7142 | 21.58 | 410 | 0.6946 | 0.4669 |
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- | 0.7113 | 22.11 | 420 | 0.6933 | 0.4669 |
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- | 0.6979 | 22.63 | 430 | 0.6934 | 0.5331 |
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- | 0.7214 | 23.16 | 440 | 0.7112 | 0.4669 |
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- | 0.6974 | 23.68 | 450 | 0.6929 | 0.5331 |
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- | 0.7077 | 24.21 | 460 | 0.6918 | 0.5331 |
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- | 0.7123 | 24.74 | 470 | 0.7006 | 0.4669 |
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- | 0.7065 | 25.26 | 480 | 0.6978 | 0.4669 |
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- | 0.7079 | 25.79 | 490 | 0.6922 | 0.5331 |
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- | 0.7063 | 26.32 | 500 | 0.6991 | 0.4669 |
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- | 0.7182 | 26.84 | 510 | 0.6956 | 0.4669 |
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- | 0.7061 | 27.37 | 520 | 0.6914 | 0.5331 |
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- | 0.7069 | 27.89 | 530 | 0.6912 | 0.5331 |
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- | 0.7024 | 28.42 | 540 | 0.6929 | 0.5331 |
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- | 0.701 | 28.95 | 550 | 0.6954 | 0.4669 |
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- | 0.7131 | 29.47 | 560 | 0.6942 | 0.4669 |
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- | 0.6999 | 30.0 | 570 | 0.6936 | 0.4669 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7483443708609272
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the crows_pairs dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.8687
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+ - Accuracy: 0.7483
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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  - train_batch_size: 64
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  - eval_batch_size: 64
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.7241 | 0.53 | 10 | 0.7015 | 0.4868 |
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+ | 0.6975 | 1.05 | 20 | 0.7124 | 0.4934 |
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+ | 0.6992 | 1.58 | 30 | 0.7102 | 0.4901 |
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+ | 0.6941 | 2.11 | 40 | 0.6890 | 0.5430 |
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+ | 0.665 | 2.63 | 50 | 0.6981 | 0.5464 |
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+ | 0.5656 | 3.16 | 60 | 0.5434 | 0.7119 |
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+ | 0.3695 | 3.68 | 70 | 0.7431 | 0.7152 |
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+ | 0.3913 | 4.21 | 80 | 0.7834 | 0.7185 |
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+ | 0.2617 | 4.74 | 90 | 0.6394 | 0.7318 |
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+ | 0.1225 | 5.26 | 100 | 0.8882 | 0.6921 |
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+ | 0.1549 | 5.79 | 110 | 0.8629 | 0.7119 |
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+ | 0.1094 | 6.32 | 120 | 1.0113 | 0.7185 |
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+ | 0.0418 | 6.84 | 130 | 1.2568 | 0.7219 |
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+ | 0.023 | 7.37 | 140 | 1.3223 | 0.7417 |
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+ | 0.045 | 7.89 | 150 | 1.5015 | 0.7086 |
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+ | 0.0216 | 8.42 | 160 | 1.1833 | 0.7550 |
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+ | 0.0084 | 8.95 | 170 | 1.4125 | 0.7318 |
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+ | 0.0198 | 9.47 | 180 | 1.5301 | 0.7152 |
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+ | 0.0061 | 10.0 | 190 | 1.3163 | 0.7483 |
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+ | 0.0041 | 10.53 | 200 | 1.3083 | 0.7517 |
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+ | 0.0046 | 11.05 | 210 | 1.4028 | 0.7616 |
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+ | 0.0034 | 11.58 | 220 | 1.5256 | 0.7583 |
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+ | 0.0012 | 12.11 | 230 | 1.6067 | 0.7583 |
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+ | 0.001 | 12.63 | 240 | 1.6199 | 0.7649 |
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+ | 0.005 | 13.16 | 250 | 1.7140 | 0.7384 |
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+ | 0.0031 | 13.68 | 260 | 1.7680 | 0.7318 |
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+ | 0.0008 | 14.21 | 270 | 1.7353 | 0.7252 |
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+ | 0.0026 | 14.74 | 280 | 1.7242 | 0.7450 |
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+ | 0.0013 | 15.26 | 290 | 1.7290 | 0.7483 |
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+ | 0.0001 | 15.79 | 300 | 1.7421 | 0.7450 |
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+ | 0.0008 | 16.32 | 310 | 1.7536 | 0.7450 |
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+ | 0.0013 | 16.84 | 320 | 1.7588 | 0.7483 |
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+ | 0.0014 | 17.37 | 330 | 1.8153 | 0.7417 |
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+ | 0.0025 | 17.89 | 340 | 1.8432 | 0.7450 |
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+ | 0.0024 | 18.42 | 350 | 1.8597 | 0.7351 |
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+ | 0.0022 | 18.95 | 360 | 1.8676 | 0.7384 |
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+ | 0.0001 | 19.47 | 370 | 1.8602 | 0.7417 |
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+ | 0.0032 | 20.0 | 380 | 1.8600 | 0.7450 |
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+ | 0.0017 | 20.53 | 390 | 1.8576 | 0.7417 |
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+ | 0.0022 | 21.05 | 400 | 1.8603 | 0.7417 |
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+ | 0.0024 | 21.58 | 410 | 1.8649 | 0.7417 |
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+ | 0.002 | 22.11 | 420 | 1.8704 | 0.7417 |
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+ | 0.0008 | 22.63 | 430 | 1.8764 | 0.7417 |
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+ | 0.0019 | 23.16 | 440 | 1.8914 | 0.7417 |
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+ | 0.0015 | 23.68 | 450 | 1.9026 | 0.7384 |
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+ | 0.0014 | 24.21 | 460 | 1.9146 | 0.7384 |
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+ | 0.0017 | 24.74 | 470 | 1.9258 | 0.7384 |
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+ | 0.0027 | 25.26 | 480 | 1.9280 | 0.7384 |
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+ | 0.0027 | 25.79 | 490 | 1.9285 | 0.7384 |
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+ | 0.001 | 26.32 | 500 | 1.9236 | 0.7384 |
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+ | 0.0034 | 26.84 | 510 | 1.8905 | 0.7450 |
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+ | 0.0013 | 27.37 | 520 | 1.8730 | 0.7417 |
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+ | 0.0016 | 27.89 | 530 | 1.8687 | 0.7450 |
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+ | 0.0007 | 28.42 | 540 | 1.8681 | 0.7483 |
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+ | 0.0042 | 28.95 | 550 | 1.8683 | 0.7483 |
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+ | 0.0009 | 29.47 | 560 | 1.8686 | 0.7483 |
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+ | 0.0018 | 30.0 | 570 | 1.8687 | 0.7483 |
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  ### Framework versions