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arabert_cross_development_task1_fold2

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bert
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  1. README.md +137 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ base_model: aubmindlab/bert-base-arabertv02
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: arabert_cross_development_task1_fold1
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+ results: []
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+ ---
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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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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # arabert_cross_development_task1_fold1
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+
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+ This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7152
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+ - Qwk: 0.1109
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+ - Mse: 0.7153
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 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: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
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+ | No log | 0.125 | 2 | 5.0133 | -0.0040 | 5.0069 |
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+ | No log | 0.25 | 4 | 1.7271 | 0.0220 | 1.7233 |
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+ | No log | 0.375 | 6 | 0.6069 | 0.0575 | 0.6049 |
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+ | No log | 0.5 | 8 | 0.6108 | 0.0838 | 0.6102 |
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+ | No log | 0.625 | 10 | 0.6811 | -0.0132 | 0.6805 |
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+ | No log | 0.75 | 12 | 0.6094 | 0.1119 | 0.6084 |
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+ | No log | 0.875 | 14 | 0.6389 | 0.0138 | 0.6386 |
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+ | No log | 1.0 | 16 | 0.6607 | -0.0302 | 0.6606 |
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+ | No log | 1.125 | 18 | 0.8561 | 0.0 | 0.8561 |
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+ | No log | 1.25 | 20 | 0.8772 | 0.0192 | 0.8774 |
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+ | No log | 1.375 | 22 | 0.6488 | 0.1233 | 0.6484 |
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+ | No log | 1.5 | 24 | 0.6095 | 0.0553 | 0.6090 |
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+ | No log | 1.625 | 26 | 0.8548 | 0.0249 | 0.8549 |
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+ | No log | 1.75 | 28 | 0.8236 | 0.0 | 0.8237 |
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+ | No log | 1.875 | 30 | 0.6385 | 0.0263 | 0.6382 |
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+ | No log | 2.0 | 32 | 0.6856 | -0.0056 | 0.6854 |
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+ | No log | 2.125 | 34 | 0.7166 | 0.0 | 0.7165 |
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+ | No log | 2.25 | 36 | 0.6505 | 0.0135 | 0.6503 |
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+ | No log | 2.375 | 38 | 0.6867 | 0.0 | 0.6865 |
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+ | No log | 2.5 | 40 | 0.7602 | 0.0 | 0.7602 |
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+ | No log | 2.625 | 42 | 0.7896 | 0.0 | 0.7897 |
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+ | No log | 2.75 | 44 | 0.8485 | 0.0 | 0.8487 |
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+ | No log | 2.875 | 46 | 0.8089 | 0.0 | 0.8090 |
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+ | No log | 3.0 | 48 | 0.8838 | 0.0 | 0.8841 |
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+ | No log | 3.125 | 50 | 1.0443 | 0.0 | 1.0448 |
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+ | No log | 3.25 | 52 | 1.2312 | 0.0 | 1.2319 |
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+ | No log | 3.375 | 54 | 1.2836 | 0.0 | 1.2843 |
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+ | No log | 3.5 | 56 | 1.0837 | 0.0 | 1.0842 |
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+ | No log | 3.625 | 58 | 0.9529 | 0.0 | 0.9532 |
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+ | No log | 3.75 | 60 | 0.9030 | 0.0 | 0.9032 |
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+ | No log | 3.875 | 62 | 0.9117 | 0.0 | 0.9119 |
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+ | No log | 4.0 | 64 | 0.8372 | 0.0 | 0.8373 |
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+ | No log | 4.125 | 66 | 0.8288 | 0.0 | 0.8289 |
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+ | No log | 4.25 | 68 | 0.7667 | 0.0 | 0.7667 |
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+ | No log | 4.375 | 70 | 0.8226 | 0.0 | 0.8228 |
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+ | No log | 4.5 | 72 | 0.9046 | 0.0 | 0.9050 |
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+ | No log | 4.625 | 74 | 1.1055 | 0.0 | 1.1061 |
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+ | No log | 4.75 | 76 | 1.1209 | 0.0 | 1.1216 |
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+ | No log | 4.875 | 78 | 0.9195 | 0.0 | 0.9199 |
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+ | No log | 5.0 | 80 | 0.7954 | 0.0554 | 0.7956 |
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+ | No log | 5.125 | 82 | 0.8199 | 0.0 | 0.8203 |
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+ | No log | 5.25 | 84 | 0.6997 | 0.1731 | 0.6999 |
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+ | No log | 5.375 | 86 | 0.6765 | 0.1731 | 0.6766 |
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+ | No log | 5.5 | 88 | 0.8095 | 0.0554 | 0.8099 |
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+ | No log | 5.625 | 90 | 0.7989 | 0.0554 | 0.7992 |
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+ | No log | 5.75 | 92 | 0.7088 | 0.1731 | 0.7089 |
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+ | No log | 5.875 | 94 | 0.8201 | 0.0554 | 0.8205 |
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+ | No log | 6.0 | 96 | 1.0195 | 0.0 | 1.0201 |
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+ | No log | 6.125 | 98 | 1.0328 | 0.0 | 1.0335 |
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+ | No log | 6.25 | 100 | 0.9344 | 0.0 | 0.9349 |
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+ | No log | 6.375 | 102 | 0.7485 | 0.0906 | 0.7487 |
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+ | No log | 6.5 | 104 | 0.6810 | 0.1387 | 0.6811 |
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+ | No log | 6.625 | 106 | 0.7638 | 0.0672 | 0.7640 |
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+ | No log | 6.75 | 108 | 0.9339 | 0.0 | 0.9342 |
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+ | No log | 6.875 | 110 | 0.9824 | 0.0 | 0.9828 |
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+ | No log | 7.0 | 112 | 0.9198 | 0.0 | 0.9202 |
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+ | No log | 7.125 | 114 | 0.8078 | 0.0554 | 0.8080 |
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+ | No log | 7.25 | 116 | 0.6480 | 0.1412 | 0.6480 |
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+ | No log | 7.375 | 118 | 0.6108 | 0.1780 | 0.6107 |
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+ | No log | 7.5 | 120 | 0.6581 | 0.1109 | 0.6581 |
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+ | No log | 7.625 | 122 | 0.7813 | 0.0554 | 0.7815 |
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+ | No log | 7.75 | 124 | 0.8870 | 0.0 | 0.8873 |
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+ | No log | 7.875 | 126 | 0.9244 | 0.0 | 0.9247 |
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+ | No log | 8.0 | 128 | 0.9045 | 0.0554 | 0.9048 |
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+ | No log | 8.125 | 130 | 0.8522 | 0.0554 | 0.8524 |
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+ | No log | 8.25 | 132 | 0.8434 | 0.0554 | 0.8436 |
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+ | No log | 8.375 | 134 | 0.8530 | 0.0554 | 0.8532 |
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+ | No log | 8.5 | 136 | 0.8770 | 0.0554 | 0.8772 |
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+ | No log | 8.625 | 138 | 0.8451 | 0.0554 | 0.8453 |
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+ | No log | 8.75 | 140 | 0.8325 | 0.0554 | 0.8327 |
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+ | No log | 8.875 | 142 | 0.8378 | 0.0554 | 0.8380 |
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+ | No log | 9.0 | 144 | 0.8214 | 0.0554 | 0.8216 |
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+ | No log | 9.125 | 146 | 0.7888 | 0.0554 | 0.7890 |
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+ | No log | 9.25 | 148 | 0.7536 | 0.0376 | 0.7537 |
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+ | No log | 9.375 | 150 | 0.7389 | 0.0612 | 0.7390 |
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+ | No log | 9.5 | 152 | 0.7209 | 0.0844 | 0.7210 |
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+ | No log | 9.625 | 154 | 0.7172 | 0.1232 | 0.7173 |
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+ | No log | 9.75 | 156 | 0.7125 | 0.1109 | 0.7126 |
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+ | No log | 9.875 | 158 | 0.7149 | 0.1109 | 0.7150 |
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+ | No log | 10.0 | 160 | 0.7152 | 0.1109 | 0.7153 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.0
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+ - Pytorch 2.4.0
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
config.json ADDED
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+ {
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+ "_name_or_path": "aubmindlab/bert-base-arabertv02",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "LABEL_0"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "LABEL_0": 0
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "regression",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.44.0",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 64000
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+ }
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