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xlnet-base-cased_crows_pairs_finetuned

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PyTorch
xlnet
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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: 0.44370860927152317
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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 [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the crows_pairs dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6984
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- - Accuracy: 0.4437
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  ## Model description
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@@ -51,38 +51,75 @@ 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: 0.01
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- - train_batch_size: 128
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  - eval_batch_size: 64
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 20
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 10 | 1.7260 | 0.4437 |
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- | No log | 2.0 | 20 | 0.6869 | 0.5563 |
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- | No log | 3.0 | 30 | 1.0103 | 0.4437 |
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- | No log | 4.0 | 40 | 0.7207 | 0.5563 |
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- | No log | 5.0 | 50 | 0.8402 | 0.4437 |
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- | No log | 6.0 | 60 | 0.7060 | 0.5563 |
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- | No log | 7.0 | 70 | 0.7714 | 0.4437 |
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- | No log | 8.0 | 80 | 0.6924 | 0.5563 |
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- | No log | 9.0 | 90 | 0.7429 | 0.4437 |
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- | No log | 10.0 | 100 | 0.6886 | 0.5563 |
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- | No log | 11.0 | 110 | 0.7110 | 0.4437 |
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- | No log | 12.0 | 120 | 0.7309 | 0.4437 |
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- | No log | 13.0 | 130 | 0.6999 | 0.5563 |
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- | No log | 14.0 | 140 | 0.6962 | 0.4437 |
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- | No log | 15.0 | 150 | 0.6869 | 0.5563 |
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- | No log | 16.0 | 160 | 0.7281 | 0.4437 |
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- | No log | 17.0 | 170 | 0.6870 | 0.5563 |
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- | No log | 18.0 | 180 | 0.7582 | 0.4437 |
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- | No log | 19.0 | 190 | 0.6998 | 0.4437 |
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- | No log | 20.0 | 200 | 0.6984 | 0.4437 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.5066225165562914
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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 [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the crows_pairs dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6932
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+ - Accuracy: 0.5066
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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: 0.0005
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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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 30
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.9006 | 0.53 | 10 | 0.7493 | 0.4934 |
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+ | 0.7565 | 1.05 | 20 | 0.7202 | 0.4934 |
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+ | 0.7303 | 1.58 | 30 | 0.6968 | 0.4934 |
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+ | 0.7495 | 2.11 | 40 | 0.7210 | 0.5066 |
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+ | 0.8008 | 2.63 | 50 | 0.6944 | 0.5066 |
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+ | 0.7251 | 3.16 | 60 | 0.6982 | 0.5066 |
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+ | 0.7193 | 3.68 | 70 | 0.7032 | 0.5066 |
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+ | 0.7118 | 4.21 | 80 | 0.6975 | 0.5066 |
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+ | 0.7419 | 4.74 | 90 | 0.7311 | 0.5066 |
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+ | 0.7175 | 5.26 | 100 | 0.6946 | 0.5066 |
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+ | 0.7293 | 5.79 | 110 | 0.7008 | 0.4934 |
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+ | 0.7208 | 6.32 | 120 | 0.6940 | 0.4934 |
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+ | 0.7101 | 6.84 | 130 | 0.6975 | 0.5066 |
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+ | 0.7138 | 7.37 | 140 | 0.7065 | 0.4934 |
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+ | 0.7112 | 7.89 | 150 | 0.6931 | 0.5066 |
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+ | 0.7093 | 8.42 | 160 | 0.6931 | 0.5066 |
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+ | 0.6996 | 8.95 | 170 | 0.6931 | 0.5066 |
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+ | 0.6948 | 9.47 | 180 | 0.7050 | 0.4934 |
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+ | 0.7118 | 10.0 | 190 | 0.6935 | 0.4934 |
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+ | 0.7015 | 10.53 | 200 | 0.6993 | 0.5066 |
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+ | 0.6985 | 11.05 | 210 | 0.6941 | 0.4934 |
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+ | 0.6983 | 11.58 | 220 | 0.7118 | 0.4934 |
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+ | 0.7031 | 12.11 | 230 | 0.7110 | 0.5066 |
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+ | 0.6987 | 12.63 | 240 | 0.7643 | 0.4934 |
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+ | 0.7483 | 13.16 | 250 | 0.7019 | 0.5066 |
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+ | 0.7065 | 13.68 | 260 | 0.7018 | 0.4934 |
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+ | 0.7008 | 14.21 | 270 | 0.6931 | 0.5066 |
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+ | 0.7074 | 14.74 | 280 | 0.6932 | 0.4934 |
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+ | 0.7097 | 15.26 | 290 | 0.6931 | 0.5066 |
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+ | 0.7284 | 15.79 | 300 | 0.6956 | 0.4934 |
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+ | 0.7045 | 16.32 | 310 | 0.6948 | 0.5066 |
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+ | 0.7041 | 16.84 | 320 | 0.7176 | 0.4934 |
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+ | 0.7118 | 17.37 | 330 | 0.6941 | 0.5066 |
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+ | 0.7044 | 17.89 | 340 | 0.6931 | 0.5066 |
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+ | 0.7034 | 18.42 | 350 | 0.6938 | 0.4934 |
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+ | 0.683 | 18.95 | 360 | 0.6984 | 0.4934 |
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+ | 0.7024 | 19.47 | 370 | 0.7009 | 0.4934 |
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+ | 0.6988 | 20.0 | 380 | 0.6999 | 0.5066 |
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+ | 0.6977 | 20.53 | 390 | 0.6974 | 0.4934 |
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+ | 0.709 | 21.05 | 400 | 0.6932 | 0.5066 |
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+ | 0.6991 | 21.58 | 410 | 0.6940 | 0.4934 |
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+ | 0.7058 | 22.11 | 420 | 0.6931 | 0.5066 |
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+ | 0.7101 | 22.63 | 430 | 0.6934 | 0.4934 |
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+ | 0.7086 | 23.16 | 440 | 0.6956 | 0.4934 |
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+ | 0.6973 | 23.68 | 450 | 0.6970 | 0.5066 |
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+ | 0.7059 | 24.21 | 460 | 0.6931 | 0.5066 |
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+ | 0.7021 | 24.74 | 470 | 0.6988 | 0.4934 |
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+ | 0.6996 | 25.26 | 480 | 0.7006 | 0.4934 |
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+ | 0.6963 | 25.79 | 490 | 0.6931 | 0.5066 |
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+ | 0.6962 | 26.32 | 500 | 0.6932 | 0.5066 |
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+ | 0.691 | 26.84 | 510 | 0.6944 | 0.4934 |
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+ | 0.7003 | 27.37 | 520 | 0.6933 | 0.4934 |
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+ | 0.6944 | 27.89 | 530 | 0.6934 | 0.4934 |
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+ | 0.6988 | 28.42 | 540 | 0.6931 | 0.5066 |
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+ | 0.7009 | 28.95 | 550 | 0.6931 | 0.5066 |
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+ | 0.699 | 29.47 | 560 | 0.6933 | 0.5066 |
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+ | 0.696 | 30.0 | 570 | 0.6932 | 0.5066 |
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  ### Framework versions