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bert-30

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bert
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bert-cased

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  1. README.md +25 -47
  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 [deepset/bert-base-cased-squad2](https://huggingface.co/deepset/bert-base-cased-squad2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 11.3111
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  ## Model description
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@@ -34,9 +34,9 @@ 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: 2e-05
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- - train_batch_size: 4
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- - eval_batch_size: 4
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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
@@ -46,49 +46,27 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 10.3108 | 0.02 | 5 | 12.3310 |
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- | 11.3688 | 0.05 | 10 | 12.2842 |
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- | 12.0992 | 0.07 | 15 | 12.2377 |
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- | 10.8808 | 0.09 | 20 | 12.1923 |
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- | 11.5554 | 0.11 | 25 | 12.1480 |
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- | 10.4562 | 0.14 | 30 | 12.1059 |
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- | 11.3704 | 0.16 | 35 | 12.0646 |
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- | 11.2796 | 0.18 | 40 | 12.0239 |
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- | 11.0892 | 0.21 | 45 | 11.9839 |
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- | 11.3659 | 0.23 | 50 | 11.9453 |
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- | 9.552 | 0.25 | 55 | 11.9083 |
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- | 10.7276 | 0.28 | 60 | 11.8726 |
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- | 10.3388 | 0.3 | 65 | 11.8381 |
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- | 11.2353 | 0.32 | 70 | 11.8045 |
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- | 11.3283 | 0.34 | 75 | 11.7717 |
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- | 10.4237 | 0.37 | 80 | 11.7398 |
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- | 11.4335 | 0.39 | 85 | 11.7099 |
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- | 10.1757 | 0.41 | 90 | 11.6803 |
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- | 10.8343 | 0.44 | 95 | 11.6522 |
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- | 10.4633 | 0.46 | 100 | 11.6252 |
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- | 11.1111 | 0.48 | 105 | 11.5994 |
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- | 10.2398 | 0.5 | 110 | 11.5743 |
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- | 10.5394 | 0.53 | 115 | 11.5506 |
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- | 10.7319 | 0.55 | 120 | 11.5279 |
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- | 9.9385 | 0.57 | 125 | 11.5065 |
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- | 9.8785 | 0.6 | 130 | 11.4861 |
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- | 10.2925 | 0.62 | 135 | 11.4670 |
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- | 10.1561 | 0.64 | 140 | 11.4492 |
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- | 10.4524 | 0.67 | 145 | 11.4327 |
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- | 10.9644 | 0.69 | 150 | 11.4166 |
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- | 10.3769 | 0.71 | 155 | 11.4020 |
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- | 10.5732 | 0.73 | 160 | 11.3882 |
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- | 9.9129 | 0.76 | 165 | 11.3757 |
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- | 10.593 | 0.78 | 170 | 11.3643 |
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- | 10.1119 | 0.8 | 175 | 11.3541 |
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- | 9.5165 | 0.83 | 180 | 11.3448 |
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- | 11.0571 | 0.85 | 185 | 11.3366 |
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- | 9.2427 | 0.87 | 190 | 11.3295 |
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- | 10.1903 | 0.89 | 195 | 11.3240 |
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- | 9.9867 | 0.92 | 200 | 11.3187 |
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- | 10.1191 | 0.94 | 205 | 11.3151 |
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- | 9.5425 | 0.96 | 210 | 11.3126 |
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- | 9.5164 | 0.99 | 215 | 11.3111 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [deepset/bert-base-cased-squad2](https://huggingface.co/deepset/bert-base-cased-squad2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 11.5401
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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-05
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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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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 10.8471 | 0.05 | 5 | 12.3076 |
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+ | 10.8298 | 0.09 | 10 | 12.2362 |
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+ | 11.0622 | 0.14 | 15 | 12.1684 |
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+ | 11.6335 | 0.18 | 20 | 12.1040 |
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+ | 11.4197 | 0.23 | 25 | 12.0427 |
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+ | 10.5672 | 0.28 | 30 | 11.9853 |
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+ | 10.7596 | 0.32 | 35 | 11.9313 |
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+ | 10.8418 | 0.37 | 40 | 11.8806 |
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+ | 11.0164 | 0.41 | 45 | 11.8333 |
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+ | 10.3409 | 0.46 | 50 | 11.7898 |
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+ | 11.2085 | 0.5 | 55 | 11.7495 |
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+ | 10.3929 | 0.55 | 60 | 11.7126 |
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+ | 9.9285 | 0.6 | 65 | 11.6798 |
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+ | 9.834 | 0.64 | 70 | 11.6507 |
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+ | 10.5704 | 0.69 | 75 | 11.6249 |
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+ | 10.8002 | 0.73 | 80 | 11.6020 |
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+ | 10.5069 | 0.78 | 85 | 11.5831 |
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+ | 10.0382 | 0.83 | 90 | 11.5671 |
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+ | 10.133 | 0.87 | 95 | 11.5551 |
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+ | 10.212 | 0.92 | 100 | 11.5459 |
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+ | 9.9872 | 0.96 | 105 | 11.5401 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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