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1670505
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bert-squad

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: hung200504/bert-squadv2
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: bert-covid-39
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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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+ # bert-covid-39
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+
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+ This model is a fine-tuned version of [hung200504/bert-squadv2](https://huggingface.co/hung200504/bert-squadv2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7252
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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: 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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+ - num_epochs: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 4.5591 | 0.03 | 5 | 1.2012 |
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+ | 1.2596 | 0.06 | 10 | 1.4381 |
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+ | 1.0125 | 0.08 | 15 | 1.0124 |
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+ | 1.2428 | 0.11 | 20 | 0.9407 |
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+ | 1.2052 | 0.14 | 25 | 0.9740 |
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+ | 0.6547 | 0.17 | 30 | 1.0313 |
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+ | 0.7966 | 0.2 | 35 | 0.9168 |
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+ | 0.8611 | 0.22 | 40 | 0.8861 |
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+ | 1.7148 | 0.25 | 45 | 0.7733 |
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+ | 1.2914 | 0.28 | 50 | 1.0139 |
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+ | 1.6152 | 0.31 | 55 | 0.7834 |
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+ | 0.9688 | 0.34 | 60 | 0.7517 |
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+ | 0.909 | 0.37 | 65 | 0.8122 |
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+ | 0.7823 | 0.39 | 70 | 0.7512 |
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+ | 0.8386 | 0.42 | 75 | 0.7157 |
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+ | 0.7884 | 0.45 | 80 | 0.7113 |
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+ | 0.9594 | 0.48 | 85 | 0.7621 |
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+ | 0.8959 | 0.51 | 90 | 0.7472 |
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+ | 0.5305 | 0.53 | 95 | 0.8187 |
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+ | 0.8252 | 0.56 | 100 | 0.7381 |
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+ | 1.6898 | 0.59 | 105 | 0.7426 |
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+ | 1.0982 | 0.62 | 110 | 0.7209 |
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+ | 1.1293 | 0.65 | 115 | 0.7321 |
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+ | 0.4554 | 0.67 | 120 | 0.6945 |
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+ | 1.2818 | 0.7 | 125 | 0.8030 |
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+ | 0.3392 | 0.73 | 130 | 0.8722 |
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+ | 1.3006 | 0.76 | 135 | 0.7928 |
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+ | 0.853 | 0.79 | 140 | 0.8538 |
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+ | 0.8214 | 0.81 | 145 | 0.8217 |
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+ | 1.0063 | 0.84 | 150 | 0.8014 |
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+ | 0.5788 | 0.87 | 155 | 0.7998 |
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+ | 0.5167 | 0.9 | 160 | 0.8472 |
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+ | 1.2736 | 0.93 | 165 | 0.7444 |
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+ | 0.5527 | 0.96 | 170 | 0.7315 |
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+ | 1.0421 | 0.98 | 175 | 0.7767 |
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+ | 0.3837 | 1.01 | 180 | 0.7005 |
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+ | 0.5765 | 1.04 | 185 | 0.7062 |
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+ | 0.6094 | 1.07 | 190 | 0.7248 |
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+ | 0.3476 | 1.1 | 195 | 0.7205 |
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+ | 0.6104 | 1.12 | 200 | 0.7028 |
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+ | 0.681 | 1.15 | 205 | 0.6956 |
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+ | 0.9434 | 1.18 | 210 | 0.7217 |
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+ | 0.3486 | 1.21 | 215 | 0.7119 |
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+ | 0.311 | 1.24 | 220 | 0.6895 |
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+ | 0.4587 | 1.26 | 225 | 0.7079 |
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+ | 0.8009 | 1.29 | 230 | 0.7364 |
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+ | 0.511 | 1.32 | 235 | 0.7349 |
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+ | 0.4046 | 1.35 | 240 | 0.7259 |
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+ | 0.6761 | 1.38 | 245 | 0.7351 |
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+ | 0.3349 | 1.4 | 250 | 0.7341 |
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+ | 0.8276 | 1.43 | 255 | 0.7304 |
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+ | 0.1637 | 1.46 | 260 | 0.7316 |
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+ | 0.2998 | 1.49 | 265 | 0.7621 |
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+ | 0.6454 | 1.52 | 270 | 0.7695 |
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+ | 0.336 | 1.54 | 275 | 0.7485 |
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+ | 0.3583 | 1.57 | 280 | 0.7430 |
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+ | 0.3906 | 1.6 | 285 | 0.7457 |
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+ | 0.6049 | 1.63 | 290 | 0.7502 |
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+ | 0.7388 | 1.66 | 295 | 0.7679 |
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+ | 0.5119 | 1.69 | 300 | 0.7832 |
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+ | 0.7891 | 1.71 | 305 | 0.7909 |
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+ | 0.5389 | 1.74 | 310 | 0.7808 |
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+ | 0.235 | 1.77 | 315 | 0.7770 |
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+ | 0.7812 | 1.8 | 320 | 0.7598 |
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+ | 0.4588 | 1.83 | 325 | 0.7491 |
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+ | 0.6632 | 1.85 | 330 | 0.7418 |
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+ | 0.8314 | 1.88 | 335 | 0.7369 |
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+ | 0.78 | 1.91 | 340 | 0.7365 |
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+ | 0.6049 | 1.94 | 345 | 0.7322 |
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+ | 0.5554 | 1.97 | 350 | 0.7271 |
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+ | 0.9808 | 1.99 | 355 | 0.7252 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.1
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+ "layer_norm_eps": 1e-12,
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