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bert-30

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bert
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bert-cased

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  1. README.md +492 -0
  2. config.json +28 -0
  3. pytorch_model.bin +3 -0
  4. special_tokens_map.json +7 -0
  5. tokenizer.json +0 -0
  6. tokenizer_config.json +58 -0
  7. training_args.bin +3 -0
  8. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ license: cc-by-4.0
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+ base_model: deepset/bert-base-cased-squad2
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: bert-30
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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-30
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+
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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: 5.4502
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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: 0.0002
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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
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 10.223 | 0.02 | 5 | 11.9913 |
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+ | 10.8523 | 0.05 | 10 | 11.5145 |
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+ | 11.086 | 0.07 | 15 | 11.0371 |
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+ | 9.6289 | 0.09 | 20 | 10.5684 |
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+ | 9.72 | 0.11 | 25 | 10.1112 |
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+ | 8.4493 | 0.14 | 30 | 9.6688 |
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+ | 8.8585 | 0.16 | 35 | 9.2391 |
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+ | 8.4229 | 0.18 | 40 | 8.8177 |
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+ | 7.8945 | 0.21 | 45 | 8.4118 |
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+ | 7.8876 | 0.23 | 50 | 8.0288 |
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+ | 6.4909 | 0.25 | 55 | 7.6809 |
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+ | 6.746 | 0.28 | 60 | 7.3743 |
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+ | 6.5319 | 0.3 | 65 | 7.0997 |
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+ | 6.634 | 0.32 | 70 | 6.8609 |
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+ | 6.2445 | 0.34 | 75 | 6.6653 |
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+ | 6.0545 | 0.37 | 80 | 6.5160 |
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+ | 6.3467 | 0.39 | 85 | 6.4028 |
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+ | 6.0512 | 0.41 | 90 | 6.3212 |
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+ | 5.7648 | 0.44 | 95 | 6.2668 |
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+ | 5.8706 | 0.46 | 100 | 6.2278 |
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+ | 5.9064 | 0.48 | 105 | 6.1932 |
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+ | 5.6687 | 0.5 | 110 | 6.1695 |
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+ | 5.7971 | 0.53 | 115 | 6.1496 |
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+ | 5.8467 | 0.55 | 120 | 6.1282 |
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+ | 5.5549 | 0.57 | 125 | 6.1093 |
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+ | 5.6604 | 0.6 | 130 | 6.0900 |
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+ | 5.7023 | 0.62 | 135 | 6.0691 |
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+ | 5.4075 | 0.64 | 140 | 6.0513 |
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+ | 5.3794 | 0.67 | 145 | 6.0366 |
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+ | 5.4388 | 0.69 | 150 | 6.0273 |
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+ | 5.5245 | 0.71 | 155 | 6.0153 |
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+ | 5.4477 | 0.73 | 160 | 6.0009 |
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+ | 5.5064 | 0.76 | 165 | 5.9854 |
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+ | 5.449 | 0.78 | 170 | 5.9681 |
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+ | 5.5521 | 0.8 | 175 | 5.9505 |
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+ | 5.4184 | 0.83 | 180 | 5.9342 |
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+ | 5.5076 | 0.85 | 185 | 5.9168 |
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+ | 5.3001 | 0.87 | 190 | 5.8997 |
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+ | 5.4266 | 0.89 | 195 | 5.8855 |
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+ | 5.303 | 0.92 | 200 | 5.8703 |
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+ | 5.1433 | 0.94 | 205 | 5.8559 |
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+ | 5.4247 | 0.96 | 210 | 5.8443 |
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+ | 5.2913 | 0.99 | 215 | 5.8347 |
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+ | 5.2319 | 1.01 | 220 | 5.8229 |
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+ | 4.9284 | 1.03 | 225 | 5.8150 |
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+ | 5.0118 | 1.06 | 230 | 5.8098 |
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+ | 5.1533 | 1.08 | 235 | 5.8078 |
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+ | 5.201 | 1.1 | 240 | 5.8056 |
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+ | 5.478 | 1.12 | 245 | 5.8026 |
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+ | 5.1066 | 1.15 | 250 | 5.7979 |
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+ | 5.4474 | 1.17 | 255 | 5.7918 |
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+ | 5.1567 | 1.19 | 260 | 5.7841 |
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+ | 5.0761 | 1.22 | 265 | 5.7812 |
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+ | 4.5299 | 1.24 | 270 | 5.7782 |
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+ | 5.1725 | 1.26 | 275 | 5.7735 |
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+ | 5.2841 | 1.28 | 280 | 5.7678 |
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+ | 5.1418 | 1.31 | 285 | 5.7614 |
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+ | 4.8134 | 1.33 | 290 | 5.7517 |
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+ | 5.0168 | 1.35 | 295 | 5.7470 |
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+ | 5.1415 | 1.38 | 300 | 5.7425 |
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+ | 4.8406 | 1.4 | 305 | 5.7409 |
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+ | 5.1648 | 1.42 | 310 | 5.7393 |
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+ | 4.6012 | 1.44 | 315 | 5.7391 |
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+ | 5.1008 | 1.47 | 320 | 5.7400 |
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+ | 4.9874 | 1.49 | 325 | 5.7420 |
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+ | 4.7481 | 1.51 | 330 | 5.7397 |
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+ | 5.0807 | 1.54 | 335 | 5.7349 |
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+ | 4.8219 | 1.56 | 340 | 5.7280 |
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+ | 5.2918 | 1.58 | 345 | 5.7196 |
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+ | 4.7966 | 1.61 | 350 | 5.7132 |
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+ | 5.1547 | 1.63 | 355 | 5.7059 |
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+ | 4.6691 | 1.65 | 360 | 5.7027 |
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+ | 4.7643 | 1.67 | 365 | 5.7022 |
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+ | 4.7299 | 1.7 | 370 | 5.7011 |
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+ | 4.8645 | 1.72 | 375 | 5.6987 |
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+ | 4.9112 | 1.74 | 380 | 5.6921 |
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+ | 4.6916 | 1.77 | 385 | 5.6878 |
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+ | 4.5665 | 1.79 | 390 | 5.6872 |
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+ | 5.0208 | 1.81 | 395 | 5.6878 |
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+ | 4.9818 | 1.83 | 400 | 5.6881 |
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+ | 4.4626 | 1.86 | 405 | 5.6891 |
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+ | 4.2459 | 1.88 | 410 | 5.6876 |
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+ | 4.389 | 1.9 | 415 | 5.6903 |
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+ | 4.4375 | 1.93 | 420 | 5.6925 |
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+ | 4.8058 | 1.95 | 425 | 5.6920 |
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+ | 4.6665 | 1.97 | 430 | 5.6879 |
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+ | 5.0375 | 2.0 | 435 | 5.6815 |
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+ | 4.7157 | 2.02 | 440 | 5.6734 |
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+ | 4.5099 | 2.04 | 445 | 5.6680 |
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+ | 4.7305 | 2.06 | 450 | 5.6628 |
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+ | 5.0492 | 2.09 | 455 | 5.6574 |
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+ | 4.2156 | 2.11 | 460 | 5.6531 |
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+ | 4.8362 | 2.13 | 465 | 5.6484 |
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+ | 4.4528 | 2.16 | 470 | 5.6506 |
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+ | 4.4387 | 2.18 | 475 | 5.6565 |
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+ | 4.7415 | 2.2 | 480 | 5.6584 |
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+ | 4.3772 | 2.22 | 485 | 5.6556 |
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+ | 4.558 | 2.25 | 490 | 5.6521 |
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+ | 4.5496 | 2.27 | 495 | 5.6495 |
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+ | 4.6056 | 2.29 | 500 | 5.6466 |
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+ | 4.9125 | 2.32 | 505 | 5.6432 |
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+ | 4.7728 | 2.34 | 510 | 5.6411 |
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+ | 4.5707 | 2.36 | 515 | 5.6424 |
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+ | 4.3599 | 2.39 | 520 | 5.6422 |
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+ | 4.2373 | 2.41 | 525 | 5.6450 |
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+ | 3.7878 | 2.43 | 530 | 5.6470 |
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+ | 4.3124 | 2.45 | 535 | 5.6491 |
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+ | 4.4129 | 2.48 | 540 | 5.6536 |
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+ | 4.1161 | 2.5 | 545 | 5.6581 |
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+ | 4.5554 | 2.52 | 550 | 5.6545 |
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+ | 4.4718 | 2.55 | 555 | 5.6501 |
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+ | 4.5906 | 2.57 | 560 | 5.6491 |
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+ | 4.3833 | 2.59 | 565 | 5.6512 |
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+ | 4.2949 | 2.61 | 570 | 5.6532 |
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+ | 4.3212 | 2.64 | 575 | 5.6584 |
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+ | 5.0496 | 2.66 | 580 | 5.6585 |
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+ | 4.5141 | 2.68 | 585 | 5.6602 |
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+ | 4.4106 | 2.71 | 590 | 5.6634 |
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+ | 4.397 | 2.73 | 595 | 5.6696 |
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+ | 4.8454 | 2.75 | 600 | 5.6738 |
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+ | 4.4965 | 2.78 | 605 | 5.6724 |
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+ | 4.129 | 2.8 | 610 | 5.6707 |
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+ | 4.433 | 2.82 | 615 | 5.6646 |
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+ | 4.5548 | 2.84 | 620 | 5.6561 |
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+ | 4.411 | 2.87 | 625 | 5.6492 |
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+ | 4.2796 | 2.89 | 630 | 5.6445 |
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+ | 4.7535 | 2.91 | 635 | 5.6377 |
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+ | 4.4193 | 2.94 | 640 | 5.6301 |
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+ | 5.0327 | 2.96 | 645 | 5.6227 |
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+ | 4.6815 | 2.98 | 650 | 5.6193 |
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+ | 4.5112 | 3.0 | 655 | 5.6178 |
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+ | 4.6954 | 3.03 | 660 | 5.6143 |
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+ | 4.691 | 3.05 | 665 | 5.6119 |
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+ | 4.6675 | 3.07 | 670 | 5.6063 |
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+ | 4.7901 | 3.1 | 675 | 5.5997 |
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+ | 4.6184 | 3.12 | 680 | 5.5925 |
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+ | 4.2704 | 3.14 | 685 | 5.5915 |
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+ | 4.3209 | 3.17 | 690 | 5.5895 |
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+ | 4.5131 | 3.19 | 695 | 5.5892 |
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+ | 4.4782 | 3.21 | 700 | 5.5895 |
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+ | 4.6145 | 3.23 | 705 | 5.5899 |
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+ | 4.3155 | 3.26 | 710 | 5.5908 |
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+ | 4.2195 | 3.28 | 715 | 5.5968 |
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+ | 4.7464 | 3.3 | 720 | 5.5977 |
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+ | 4.4204 | 3.33 | 725 | 5.6000 |
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+ | 4.3541 | 3.35 | 730 | 5.6034 |
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+ | 4.0531 | 3.37 | 735 | 5.6073 |
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+ | 4.1244 | 3.39 | 740 | 5.6110 |
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+ | 4.4016 | 3.42 | 745 | 5.6131 |
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+ | 4.1842 | 3.44 | 750 | 5.6155 |
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+ | 4.4012 | 3.46 | 755 | 5.6199 |
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+ | 4.3157 | 3.49 | 760 | 5.6278 |
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+ | 4.5788 | 3.51 | 765 | 5.6357 |
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+ | 4.0343 | 3.53 | 770 | 5.6433 |
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+ | 4.2088 | 3.56 | 775 | 5.6463 |
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+ | 4.4668 | 3.58 | 780 | 5.6464 |
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+ | 4.1564 | 3.6 | 785 | 5.6514 |
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+ | 4.6138 | 3.62 | 790 | 5.6527 |
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+ | 4.0778 | 3.65 | 795 | 5.6516 |
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+ | 4.9551 | 3.67 | 800 | 5.6485 |
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+ | 4.7297 | 3.69 | 805 | 5.6459 |
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+ | 4.2442 | 3.72 | 810 | 5.6444 |
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+ | 4.42 | 3.74 | 815 | 5.6414 |
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+ | 3.8831 | 3.76 | 820 | 5.6408 |
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+ | 4.4075 | 3.78 | 825 | 5.6400 |
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+ | 4.5851 | 3.81 | 830 | 5.6300 |
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+ | 4.2949 | 3.83 | 835 | 5.6189 |
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+ | 3.8835 | 3.85 | 840 | 5.6134 |
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+ | 4.1109 | 3.88 | 845 | 5.6094 |
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+ | 4.845 | 3.9 | 850 | 5.6011 |
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+ | 4.4053 | 3.92 | 855 | 5.5883 |
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+ | 4.1683 | 3.94 | 860 | 5.5803 |
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+ | 3.9257 | 3.97 | 865 | 5.5762 |
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+ | 4.0174 | 3.99 | 870 | 5.5797 |
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+ | 3.8825 | 4.01 | 875 | 5.5854 |
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+ | 4.3911 | 4.04 | 880 | 5.5896 |
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+ | 4.5066 | 4.06 | 885 | 5.5873 |
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+ | 4.3192 | 4.08 | 890 | 5.5818 |
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+ | 4.8764 | 4.11 | 895 | 5.5771 |
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+ | 4.3541 | 4.13 | 900 | 5.5724 |
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+ | 4.7328 | 4.15 | 905 | 5.5685 |
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+ | 3.9713 | 4.17 | 910 | 5.5657 |
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+ | 4.3436 | 4.2 | 915 | 5.5640 |
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+ | 4.6016 | 4.22 | 920 | 5.5671 |
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+ | 4.7167 | 4.24 | 925 | 5.5666 |
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+ | 4.6485 | 4.27 | 930 | 5.5664 |
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+ | 4.3609 | 4.29 | 935 | 5.5629 |
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+ | 4.5688 | 4.31 | 940 | 5.5582 |
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+ | 3.6015 | 4.33 | 945 | 5.5605 |
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+ | 3.8749 | 4.36 | 950 | 5.5666 |
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+ | 3.9043 | 4.38 | 955 | 5.5697 |
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+ | 4.7317 | 4.4 | 960 | 5.5697 |
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+ | 4.4383 | 4.43 | 965 | 5.5649 |
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+ | 4.5584 | 4.45 | 970 | 5.5560 |
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+ | 4.3123 | 4.47 | 975 | 5.5467 |
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+ | 3.9965 | 4.5 | 980 | 5.5418 |
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+ | 4.3387 | 4.52 | 985 | 5.5382 |
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+ | 3.26 | 4.54 | 990 | 5.5385 |
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+ | 4.4314 | 4.56 | 995 | 5.5390 |
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+ | 4.2901 | 4.59 | 1000 | 5.5375 |
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+ | 4.0901 | 4.61 | 1005 | 5.5355 |
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+ | 4.3606 | 4.63 | 1010 | 5.5362 |
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+ | 3.9168 | 4.66 | 1015 | 5.5373 |
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+ | 4.539 | 4.68 | 1020 | 5.5382 |
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+ | 4.3531 | 4.7 | 1025 | 5.5422 |
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+ | 4.1748 | 4.72 | 1030 | 5.5461 |
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+ | 4.1432 | 4.75 | 1035 | 5.5484 |
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+ | 3.9481 | 4.77 | 1040 | 5.5502 |
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+ | 4.7143 | 4.79 | 1045 | 5.5492 |
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+ | 4.4564 | 4.82 | 1050 | 5.5454 |
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+ | 4.4885 | 4.84 | 1055 | 5.5389 |
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+ | 4.1448 | 4.86 | 1060 | 5.5344 |
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+ | 4.0414 | 4.89 | 1065 | 5.5308 |
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+ | 4.174 | 4.91 | 1070 | 5.5267 |
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+ | 3.8038 | 4.93 | 1075 | 5.5267 |
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+ | 4.6791 | 4.95 | 1080 | 5.5281 |
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+ | 4.1429 | 4.98 | 1085 | 5.5289 |
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+ | 3.8355 | 5.0 | 1090 | 5.5321 |
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+ | 3.9843 | 5.02 | 1095 | 5.5337 |
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+ | 3.9889 | 5.05 | 1100 | 5.5375 |
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+ | 4.0622 | 5.07 | 1105 | 5.5403 |
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+ | 4.8474 | 5.09 | 1110 | 5.5395 |
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+ | 4.0241 | 5.11 | 1115 | 5.5403 |
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+ | 4.0762 | 5.14 | 1120 | 5.5439 |
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+ | 4.4967 | 5.16 | 1125 | 5.5442 |
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+ | 3.774 | 5.18 | 1130 | 5.5420 |
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+ | 4.3855 | 5.21 | 1135 | 5.5394 |
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+ | 3.8964 | 5.23 | 1140 | 5.5364 |
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+ | 4.2257 | 5.25 | 1145 | 5.5337 |
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+ | 4.1188 | 5.28 | 1150 | 5.5301 |
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+ | 4.7414 | 5.3 | 1155 | 5.5251 |
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+ | 4.0087 | 5.32 | 1160 | 5.5238 |
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+ | 3.9588 | 5.34 | 1165 | 5.5226 |
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+ | 4.3741 | 5.37 | 1170 | 5.5220 |
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+ | 4.3756 | 5.39 | 1175 | 5.5218 |
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+ | 4.3859 | 5.41 | 1180 | 5.5222 |
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+ | 4.2934 | 5.44 | 1185 | 5.5208 |
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+ | 4.2357 | 5.46 | 1190 | 5.5197 |
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+ | 4.1551 | 5.48 | 1195 | 5.5202 |
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+ | 4.1445 | 5.5 | 1200 | 5.5217 |
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+ | 4.2856 | 5.53 | 1205 | 5.5227 |
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+ | 4.1534 | 5.55 | 1210 | 5.5238 |
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+ | 4.3472 | 5.57 | 1215 | 5.5209 |
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+ | 4.2422 | 5.6 | 1220 | 5.5182 |
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+ | 4.578 | 5.62 | 1225 | 5.5173 |
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+ | 4.6536 | 5.64 | 1230 | 5.5153 |
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+ | 3.997 | 5.67 | 1235 | 5.5114 |
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+ | 4.0307 | 5.69 | 1240 | 5.5090 |
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+ | 3.9198 | 5.71 | 1245 | 5.5113 |
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+ | 4.3694 | 5.73 | 1250 | 5.5141 |
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+ | 4.2031 | 5.76 | 1255 | 5.5158 |
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+ | 4.0642 | 5.78 | 1260 | 5.5172 |
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+ | 3.8952 | 5.8 | 1265 | 5.5184 |
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+ | 3.8807 | 5.83 | 1270 | 5.5204 |
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+ | 4.209 | 5.85 | 1275 | 5.5186 |
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+ | 4.0276 | 5.87 | 1280 | 5.5134 |
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+ | 4.5011 | 5.89 | 1285 | 5.5076 |
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+ | 4.5032 | 5.92 | 1290 | 5.5014 |
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+ | 4.0724 | 5.94 | 1295 | 5.4960 |
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+ | 4.3952 | 5.96 | 1300 | 5.4922 |
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+ | 3.9391 | 5.99 | 1305 | 5.4887 |
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+ | 4.5013 | 6.01 | 1310 | 5.4882 |
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+ | 3.7748 | 6.03 | 1315 | 5.4890 |
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+ | 4.1817 | 6.06 | 1320 | 5.4898 |
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+ | 4.4581 | 6.08 | 1325 | 5.4897 |
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+ | 3.7311 | 6.1 | 1330 | 5.4902 |
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+ | 4.0439 | 6.12 | 1335 | 5.4910 |
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+ | 3.8044 | 6.15 | 1340 | 5.4924 |
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+ | 3.8836 | 6.17 | 1345 | 5.4932 |
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+ | 4.0835 | 6.19 | 1350 | 5.4952 |
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+ | 3.8672 | 6.22 | 1355 | 5.4979 |
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+ | 3.8561 | 6.24 | 1360 | 5.5016 |
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+ | 3.9088 | 6.26 | 1365 | 5.5073 |
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+ | 4.5821 | 6.28 | 1370 | 5.5111 |
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+ | 4.5992 | 6.31 | 1375 | 5.5128 |
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+ | 4.1571 | 6.33 | 1380 | 5.5115 |
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+ | 4.4918 | 6.35 | 1385 | 5.5088 |
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+ | 4.8008 | 6.38 | 1390 | 5.5020 |
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+ | 4.3536 | 6.4 | 1395 | 5.4963 |
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+ | 3.5612 | 6.42 | 1400 | 5.4946 |
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+ | 4.2318 | 6.44 | 1405 | 5.4949 |
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+ | 4.1321 | 6.47 | 1410 | 5.4931 |
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+ | 4.0747 | 6.49 | 1415 | 5.4935 |
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+ | 3.5846 | 6.51 | 1420 | 5.4974 |
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+ | 4.5849 | 6.54 | 1425 | 5.4998 |
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+ | 4.7748 | 6.56 | 1430 | 5.4980 |
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+ | 4.3293 | 6.58 | 1435 | 5.4938 |
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+ | 3.862 | 6.61 | 1440 | 5.4925 |
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+ | 4.561 | 6.63 | 1445 | 5.4904 |
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+ | 4.3999 | 6.65 | 1450 | 5.4883 |
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+ | 4.0645 | 6.67 | 1455 | 5.4869 |
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+ | 4.4209 | 6.7 | 1460 | 5.4863 |
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+ | 4.0743 | 6.72 | 1465 | 5.4824 |
342
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344
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355
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+
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+
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+ ### Framework versions
488
+
489
+ - Transformers 4.34.1
490
+ - Pytorch 2.0.1+cu118
491
+ - Datasets 2.14.5
492
+ - Tokenizers 0.14.1
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