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bert-30

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bert
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bert-cased

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  1. README.md +60 -10
  2. pytorch_model.bin +2 -2
  3. training_args.bin +2 -2
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: 12.1456
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  ## Model description
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@@ -35,27 +35,77 @@ More information needed
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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: 32
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- - eval_batch_size: 32
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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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- | 11.2227 | 0.18 | 5 | 12.3080 |
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- | 10.9657 | 0.36 | 10 | 12.2462 |
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- | 11.1174 | 0.54 | 15 | 12.1988 |
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- | 10.8921 | 0.71 | 20 | 12.1654 |
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- | 10.8109 | 0.89 | 25 | 12.1456 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.34.1
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- - Pytorch 2.0.1+cu118
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  - Datasets 2.14.5
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  - Tokenizers 0.14.1
 
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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: 10.2691
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  ## Model description
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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: 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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 11.3132 | 0.09 | 5 | 12.3055 |
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+ | 11.4109 | 0.18 | 10 | 12.2292 |
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+ | 10.9744 | 0.27 | 15 | 12.1547 |
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+ | 11.0771 | 0.36 | 20 | 12.0814 |
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+ | 11.0342 | 0.45 | 25 | 12.0101 |
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+ | 11.0327 | 0.55 | 30 | 11.9396 |
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+ | 10.2954 | 0.64 | 35 | 11.8706 |
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+ | 10.8979 | 0.73 | 40 | 11.8043 |
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+ | 10.432 | 0.82 | 45 | 11.7386 |
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+ | 10.3023 | 0.91 | 50 | 11.6747 |
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+ | 10.0494 | 1.0 | 55 | 11.6128 |
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+ | 10.2273 | 1.09 | 60 | 11.5521 |
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+ | 10.3139 | 1.18 | 65 | 11.4931 |
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+ | 10.5075 | 1.27 | 70 | 11.4349 |
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+ | 10.0234 | 1.36 | 75 | 11.3790 |
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+ | 10.4276 | 1.45 | 80 | 11.3238 |
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+ | 10.1397 | 1.55 | 85 | 11.2699 |
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+ | 10.0675 | 1.64 | 90 | 11.2174 |
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+ | 9.8835 | 1.73 | 95 | 11.1665 |
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+ | 10.0738 | 1.82 | 100 | 11.1169 |
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+ | 9.6112 | 1.91 | 105 | 11.0687 |
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+ | 9.9186 | 2.0 | 110 | 11.0227 |
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+ | 9.8411 | 2.09 | 115 | 10.9779 |
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+ | 9.6506 | 2.18 | 120 | 10.9342 |
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+ | 9.7831 | 2.27 | 125 | 10.8916 |
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+ | 9.8835 | 2.36 | 130 | 10.8509 |
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+ | 9.4752 | 2.45 | 135 | 10.8111 |
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+ | 9.8176 | 2.55 | 140 | 10.7731 |
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+ | 9.3628 | 2.64 | 145 | 10.7369 |
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+ | 9.819 | 2.73 | 150 | 10.7017 |
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+ | 9.572 | 2.82 | 155 | 10.6681 |
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+ | 9.522 | 2.91 | 160 | 10.6356 |
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+ | 9.6874 | 3.0 | 165 | 10.6046 |
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+ | 9.6037 | 3.09 | 170 | 10.5750 |
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+ | 9.5624 | 3.18 | 175 | 10.5468 |
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+ | 9.2702 | 3.27 | 180 | 10.5202 |
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+ | 9.1347 | 3.36 | 185 | 10.4947 |
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+ | 9.8154 | 3.45 | 190 | 10.4706 |
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+ | 9.4045 | 3.55 | 195 | 10.4475 |
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+ | 9.2453 | 3.64 | 200 | 10.4262 |
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+ | 9.1087 | 3.73 | 205 | 10.4062 |
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+ | 8.985 | 3.82 | 210 | 10.3875 |
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+ | 9.0054 | 3.91 | 215 | 10.3705 |
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+ | 9.4764 | 4.0 | 220 | 10.3545 |
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+ | 9.13 | 4.09 | 225 | 10.3401 |
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+ | 9.4397 | 4.18 | 230 | 10.3272 |
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+ | 9.0841 | 4.27 | 235 | 10.3153 |
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+ | 9.5885 | 4.36 | 240 | 10.3048 |
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+ | 9.4137 | 4.45 | 245 | 10.2958 |
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+ | 9.1068 | 4.55 | 250 | 10.2878 |
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+ | 9.1388 | 4.64 | 255 | 10.2816 |
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+ | 8.8014 | 4.73 | 260 | 10.2763 |
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+ | 8.9782 | 4.82 | 265 | 10.2727 |
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+ | 9.222 | 4.91 | 270 | 10.2701 |
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+ | 9.292 | 5.0 | 275 | 10.2691 |
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  ### Framework versions
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  - Transformers 4.34.1
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+ - Pytorch 2.1.0+cu118
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  - Datasets 2.14.5
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  - Tokenizers 0.14.1
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