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bert-31

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bert-cased

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  1. README.md +48 -16
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [hung200504/bert-21](https://huggingface.co/hung200504/bert-21) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 11.7886
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  ## Model description
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@@ -34,29 +34,61 @@ 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: 5e-07
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- - train_batch_size: 16
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- - eval_batch_size: 16
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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: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 10.9038 | 0.09 | 5 | 11.9125 |
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- | 11.0402 | 0.18 | 10 | 11.8894 |
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- | 10.6622 | 0.27 | 15 | 11.8688 |
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- | 10.8103 | 0.36 | 20 | 11.8506 |
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- | 10.8199 | 0.45 | 25 | 11.8350 |
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- | 10.8686 | 0.55 | 30 | 11.8212 |
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- | 10.1809 | 0.64 | 35 | 11.8099 |
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- | 10.8401 | 0.73 | 40 | 11.8011 |
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- | 10.4191 | 0.82 | 45 | 11.7948 |
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- | 10.3479 | 0.91 | 50 | 11.7906 |
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- | 10.1366 | 1.0 | 55 | 11.7886 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [hung200504/bert-21](https://huggingface.co/hung200504/bert-21) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 11.6244
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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: 3e-07
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 10.4595 | 0.05 | 5 | 11.9220 |
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+ | 10.4917 | 0.09 | 10 | 11.9078 |
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+ | 10.7603 | 0.14 | 15 | 11.8942 |
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+ | 11.3788 | 0.18 | 20 | 11.8816 |
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+ | 11.2043 | 0.23 | 25 | 11.8684 |
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+ | 10.4152 | 0.28 | 30 | 11.8558 |
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+ | 10.6386 | 0.32 | 35 | 11.8436 |
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+ | 10.7594 | 0.37 | 40 | 11.8319 |
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+ | 10.9593 | 0.41 | 45 | 11.8201 |
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+ | 10.3177 | 0.46 | 50 | 11.8090 |
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+ | 11.2145 | 0.5 | 55 | 11.7982 |
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+ | 10.4266 | 0.55 | 60 | 11.7877 |
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+ | 9.9668 | 0.6 | 65 | 11.7774 |
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+ | 9.8843 | 0.64 | 70 | 11.7681 |
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+ | 10.6546 | 0.69 | 75 | 11.7585 |
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+ | 10.9206 | 0.73 | 80 | 11.7497 |
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+ | 10.5989 | 0.78 | 85 | 11.7411 |
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+ | 10.1503 | 0.83 | 90 | 11.7322 |
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+ | 10.241 | 0.87 | 95 | 11.7242 |
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+ | 10.3243 | 0.92 | 100 | 11.7163 |
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+ | 10.0939 | 0.96 | 105 | 11.7089 |
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+ | 10.2936 | 1.01 | 110 | 11.7015 |
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+ | 9.8946 | 1.06 | 115 | 11.6947 |
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+ | 10.806 | 1.1 | 120 | 11.6880 |
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+ | 10.3278 | 1.15 | 125 | 11.6818 |
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+ | 9.9841 | 1.19 | 130 | 11.6760 |
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+ | 10.375 | 1.24 | 135 | 11.6701 |
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+ | 10.7491 | 1.28 | 140 | 11.6654 |
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+ | 10.0501 | 1.33 | 145 | 11.6600 |
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+ | 10.4491 | 1.38 | 150 | 11.6553 |
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+ | 9.9726 | 1.42 | 155 | 11.6511 |
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+ | 10.2234 | 1.47 | 160 | 11.6471 |
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+ | 10.2598 | 1.51 | 165 | 11.6434 |
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+ | 9.9445 | 1.56 | 170 | 11.6407 |
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+ | 9.9564 | 1.61 | 175 | 11.6372 |
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+ | 10.7074 | 1.65 | 180 | 11.6345 |
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+ | 10.7075 | 1.7 | 185 | 11.6321 |
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+ | 10.3899 | 1.74 | 190 | 11.6301 |
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+ | 10.5313 | 1.79 | 195 | 11.6285 |
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+ | 10.8444 | 1.83 | 200 | 11.6271 |
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+ | 10.8303 | 1.88 | 205 | 11.6257 |
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+ | 10.7634 | 1.93 | 210 | 11.6249 |
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+ | 10.237 | 1.97 | 215 | 11.6244 |
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  ### Framework versions
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