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  1. README.md +228 -0
  2. config.json +33 -0
  3. model.safetensors +3 -0
  4. runs/Aug22_10-22-58_0095ffe889f2/events.out.tfevents.1724322179.0095ffe889f2.25.0 +3 -0
  5. runs/Aug22_10-45-22_0095ffe889f2/events.out.tfevents.1724323523.0095ffe889f2.25.1 +3 -0
  6. runs/Aug22_11-07-47_0095ffe889f2/events.out.tfevents.1724324868.0095ffe889f2.25.2 +3 -0
  7. runs/Aug22_11-30-11_0095ffe889f2/events.out.tfevents.1724326212.0095ffe889f2.25.3 +3 -0
  8. runs/Aug22_11-52-37_0095ffe889f2/events.out.tfevents.1724327557.0095ffe889f2.25.4 +3 -0
  9. runs/Aug22_12-15-04_0095ffe889f2/events.out.tfevents.1724328905.0095ffe889f2.25.5 +3 -0
  10. runs/Aug22_12-38-55_0095ffe889f2/events.out.tfevents.1724330336.0095ffe889f2.25.6 +3 -0
  11. runs/Aug22_13-02-35_0095ffe889f2/events.out.tfevents.1724331756.0095ffe889f2.25.7 +3 -0
  12. runs/Aug22_13-26-05_0095ffe889f2/events.out.tfevents.1724333166.0095ffe889f2.25.8 +3 -0
  13. runs/Aug22_13-49-43_0095ffe889f2/events.out.tfevents.1724334584.0095ffe889f2.25.9 +3 -0
  14. runs/Aug22_14-13-13_0095ffe889f2/events.out.tfevents.1724335995.0095ffe889f2.25.10 +3 -0
  15. runs/Aug22_14-37-26_0095ffe889f2/events.out.tfevents.1724337447.0095ffe889f2.25.11 +3 -0
  16. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google-bert/bert-base-cased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: bert_baseline_prompt_adherence_task5_fold0
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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_baseline_prompt_adherence_task5_fold0
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+
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+ This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4870
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+ - Qwk: 0.7160
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+ - Mse: 0.4874
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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: 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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+
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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 | 0.0294 | 2 | 3.1421 | 0.0 | 3.1416 |
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+ | No log | 0.0588 | 4 | 2.4083 | 0.0030 | 2.4077 |
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+ | No log | 0.0882 | 6 | 1.8695 | 0.1157 | 1.8689 |
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+ | No log | 0.1176 | 8 | 1.4999 | 0.0197 | 1.4992 |
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+ | No log | 0.1471 | 10 | 1.2033 | 0.0 | 1.2027 |
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+ | No log | 0.1765 | 12 | 1.0581 | 0.0 | 1.0575 |
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+ | No log | 0.2059 | 14 | 0.9734 | 0.4026 | 0.9728 |
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+ | No log | 0.2353 | 16 | 0.9439 | 0.3348 | 0.9435 |
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+ | No log | 0.2647 | 18 | 0.9011 | 0.3514 | 0.9007 |
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+ | No log | 0.2941 | 20 | 0.8612 | 0.3899 | 0.8606 |
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+ | No log | 0.3235 | 22 | 0.8436 | 0.3677 | 0.8430 |
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+ | No log | 0.3529 | 24 | 0.7792 | 0.4120 | 0.7789 |
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+ | No log | 0.3824 | 26 | 0.7411 | 0.4097 | 0.7412 |
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+ | No log | 0.4118 | 28 | 0.7178 | 0.4104 | 0.7181 |
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+ | No log | 0.4412 | 30 | 0.6881 | 0.4144 | 0.6884 |
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+ | No log | 0.4706 | 32 | 0.6386 | 0.4233 | 0.6388 |
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+ | No log | 0.5 | 34 | 0.6263 | 0.4260 | 0.6267 |
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+ | No log | 0.5294 | 36 | 0.6191 | 0.4425 | 0.6196 |
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+ | No log | 0.5588 | 38 | 0.6170 | 0.4483 | 0.6176 |
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+ | No log | 0.5882 | 40 | 0.6557 | 0.4512 | 0.6564 |
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+ | No log | 0.6176 | 42 | 0.7423 | 0.4366 | 0.7432 |
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+ | No log | 0.6471 | 44 | 0.6778 | 0.4875 | 0.6785 |
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+ | No log | 0.6765 | 46 | 0.5894 | 0.5210 | 0.5899 |
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+ | No log | 0.7059 | 48 | 0.5643 | 0.5377 | 0.5645 |
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+ | No log | 0.7353 | 50 | 0.5833 | 0.5055 | 0.5831 |
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+ | No log | 0.7647 | 52 | 0.5574 | 0.5158 | 0.5574 |
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+ | No log | 0.7941 | 54 | 0.5871 | 0.6693 | 0.5878 |
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+ | No log | 0.8235 | 56 | 0.6332 | 0.6972 | 0.6341 |
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+ | No log | 0.8529 | 58 | 0.5675 | 0.6386 | 0.5680 |
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+ | No log | 0.8824 | 60 | 0.5659 | 0.6737 | 0.5665 |
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+ | No log | 0.9118 | 62 | 0.5687 | 0.6856 | 0.5691 |
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+ | No log | 0.9412 | 64 | 0.6101 | 0.7011 | 0.6109 |
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+ | No log | 0.9706 | 66 | 0.6053 | 0.7360 | 0.6061 |
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+ | No log | 1.0 | 68 | 0.5455 | 0.6771 | 0.5459 |
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+ | No log | 1.0294 | 70 | 0.5344 | 0.6306 | 0.5346 |
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+ | No log | 1.0588 | 72 | 0.5456 | 0.6483 | 0.5459 |
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+ | No log | 1.0882 | 74 | 0.5758 | 0.6801 | 0.5762 |
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+ | No log | 1.1176 | 76 | 0.6070 | 0.7361 | 0.6077 |
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+ | No log | 1.1471 | 78 | 0.6643 | 0.7415 | 0.6652 |
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+ | No log | 1.1765 | 80 | 0.6498 | 0.7262 | 0.6506 |
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+ | No log | 1.2059 | 82 | 0.5447 | 0.6309 | 0.5449 |
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+ | No log | 1.2353 | 84 | 0.5707 | 0.5635 | 0.5703 |
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+ | No log | 1.2647 | 86 | 0.5895 | 0.5689 | 0.5890 |
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+ | No log | 1.2941 | 88 | 0.5714 | 0.6711 | 0.5718 |
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+ | No log | 1.3235 | 90 | 0.5937 | 0.7027 | 0.5946 |
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+ | No log | 1.3529 | 92 | 0.5348 | 0.6453 | 0.5352 |
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+ | No log | 1.3824 | 94 | 0.5234 | 0.6111 | 0.5234 |
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+ | No log | 1.4118 | 96 | 0.5613 | 0.7067 | 0.5622 |
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+ | No log | 1.4412 | 98 | 0.6330 | 0.7364 | 0.6342 |
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+ | No log | 1.4706 | 100 | 0.6118 | 0.7386 | 0.6128 |
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+ | No log | 1.5 | 102 | 0.5264 | 0.6980 | 0.5269 |
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+ | No log | 1.5294 | 104 | 0.5054 | 0.6064 | 0.5052 |
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+ | No log | 1.5588 | 106 | 0.5020 | 0.6057 | 0.5019 |
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+ | No log | 1.5882 | 108 | 0.4930 | 0.6402 | 0.4932 |
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+ | No log | 1.6176 | 110 | 0.5124 | 0.6965 | 0.5130 |
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+ | No log | 1.6471 | 112 | 0.5059 | 0.7021 | 0.5065 |
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+ | No log | 1.6765 | 114 | 0.4952 | 0.6826 | 0.4957 |
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+ | No log | 1.7059 | 116 | 0.4838 | 0.6611 | 0.4842 |
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+ | No log | 1.7353 | 118 | 0.4787 | 0.6423 | 0.4789 |
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+ | No log | 1.7647 | 120 | 0.4822 | 0.6561 | 0.4826 |
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+ | No log | 1.7941 | 122 | 0.5205 | 0.7345 | 0.5212 |
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+ | No log | 1.8235 | 124 | 0.5129 | 0.7314 | 0.5135 |
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+ | No log | 1.8529 | 126 | 0.4845 | 0.6544 | 0.4847 |
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+ | No log | 1.8824 | 128 | 0.4865 | 0.6634 | 0.4868 |
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+ | No log | 1.9118 | 130 | 0.4838 | 0.6358 | 0.4839 |
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+ | No log | 1.9412 | 132 | 0.4898 | 0.6777 | 0.4900 |
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+ | No log | 1.9706 | 134 | 0.4804 | 0.6655 | 0.4806 |
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+ | No log | 2.0 | 136 | 0.4804 | 0.5760 | 0.4800 |
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+ | No log | 2.0294 | 138 | 0.4835 | 0.5762 | 0.4831 |
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+ | No log | 2.0588 | 140 | 0.4624 | 0.6260 | 0.4623 |
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+ | No log | 2.0882 | 142 | 0.5061 | 0.7344 | 0.5067 |
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+ | No log | 2.1176 | 144 | 0.5440 | 0.7385 | 0.5448 |
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+ | No log | 2.1471 | 146 | 0.5168 | 0.7265 | 0.5174 |
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+ | No log | 2.1765 | 148 | 0.4591 | 0.6554 | 0.4592 |
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+ | No log | 2.2059 | 150 | 0.4728 | 0.5767 | 0.4724 |
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+ | No log | 2.2353 | 152 | 0.5080 | 0.5478 | 0.5073 |
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+ | No log | 2.2647 | 154 | 0.4907 | 0.5525 | 0.4902 |
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+ | No log | 2.2941 | 156 | 0.4599 | 0.5955 | 0.4598 |
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+ | No log | 2.3235 | 158 | 0.4861 | 0.7290 | 0.4865 |
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+ | No log | 2.3529 | 160 | 0.6133 | 0.7618 | 0.6143 |
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+ | No log | 2.3824 | 162 | 0.7415 | 0.7608 | 0.7430 |
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+ | No log | 2.4118 | 164 | 0.7229 | 0.7630 | 0.7243 |
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+ | No log | 2.4412 | 166 | 0.6094 | 0.7553 | 0.6104 |
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+ | No log | 2.4706 | 168 | 0.4935 | 0.7226 | 0.4939 |
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+ | No log | 2.5 | 170 | 0.4734 | 0.6028 | 0.4730 |
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+ | No log | 2.5294 | 172 | 0.4959 | 0.5787 | 0.4952 |
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+ | No log | 2.5588 | 174 | 0.4736 | 0.5908 | 0.4732 |
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+ | No log | 2.5882 | 176 | 0.4659 | 0.6921 | 0.4661 |
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+ | No log | 2.6176 | 178 | 0.5161 | 0.7449 | 0.5168 |
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+ | No log | 2.6471 | 180 | 0.5802 | 0.7581 | 0.5812 |
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+ | No log | 2.6765 | 182 | 0.5806 | 0.7602 | 0.5816 |
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+ | No log | 2.7059 | 184 | 0.5066 | 0.7403 | 0.5073 |
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+ | No log | 2.7353 | 186 | 0.4652 | 0.6848 | 0.4654 |
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+ | No log | 2.7647 | 188 | 0.4526 | 0.6386 | 0.4525 |
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+ | No log | 2.7941 | 190 | 0.4537 | 0.6420 | 0.4536 |
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+ | No log | 2.8235 | 192 | 0.4627 | 0.6977 | 0.4629 |
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+ | No log | 2.8529 | 194 | 0.4899 | 0.7249 | 0.4904 |
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+ | No log | 2.8824 | 196 | 0.5294 | 0.7309 | 0.5302 |
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+ | No log | 2.9118 | 198 | 0.5313 | 0.7249 | 0.5321 |
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+ | No log | 2.9412 | 200 | 0.4939 | 0.7241 | 0.4944 |
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+ | No log | 2.9706 | 202 | 0.4574 | 0.6735 | 0.4573 |
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+ | No log | 3.0 | 204 | 0.4569 | 0.6519 | 0.4567 |
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+ | No log | 3.0294 | 206 | 0.4649 | 0.6639 | 0.4647 |
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+ | No log | 3.0588 | 208 | 0.4917 | 0.7097 | 0.4920 |
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+ | No log | 3.0882 | 210 | 0.5072 | 0.7189 | 0.5076 |
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+ | No log | 3.1176 | 212 | 0.5108 | 0.7087 | 0.5111 |
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+ | No log | 3.1471 | 214 | 0.4959 | 0.6660 | 0.4957 |
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+ | No log | 3.1765 | 216 | 0.4845 | 0.6598 | 0.4841 |
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+ | No log | 3.2059 | 218 | 0.4681 | 0.6549 | 0.4678 |
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+ | No log | 3.2353 | 220 | 0.4605 | 0.6981 | 0.4605 |
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+ | No log | 3.2647 | 222 | 0.4876 | 0.7221 | 0.4881 |
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+ | No log | 3.2941 | 224 | 0.5067 | 0.7194 | 0.5072 |
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+ | No log | 3.3235 | 226 | 0.4901 | 0.7133 | 0.4905 |
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+ | No log | 3.3529 | 228 | 0.4686 | 0.6839 | 0.4687 |
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+ | No log | 3.3824 | 230 | 0.4717 | 0.6952 | 0.4719 |
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+ | No log | 3.4118 | 232 | 0.4693 | 0.6941 | 0.4694 |
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+ | No log | 3.4412 | 234 | 0.4836 | 0.7163 | 0.4839 |
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+ | No log | 3.4706 | 236 | 0.4918 | 0.7138 | 0.4921 |
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+ | No log | 3.5 | 238 | 0.4993 | 0.7236 | 0.4996 |
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+ | No log | 3.5294 | 240 | 0.5378 | 0.7311 | 0.5384 |
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+ | No log | 3.5588 | 242 | 0.5550 | 0.7422 | 0.5557 |
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+ | No log | 3.5882 | 244 | 0.5267 | 0.7269 | 0.5272 |
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+ | No log | 3.6176 | 246 | 0.4938 | 0.7017 | 0.4939 |
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+ | No log | 3.6471 | 248 | 0.4934 | 0.7103 | 0.4935 |
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+ | No log | 3.6765 | 250 | 0.4943 | 0.7111 | 0.4945 |
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+ | No log | 3.7059 | 252 | 0.4932 | 0.7133 | 0.4934 |
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+ | No log | 3.7353 | 254 | 0.4942 | 0.7149 | 0.4945 |
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+ | No log | 3.7647 | 256 | 0.5095 | 0.7269 | 0.5102 |
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+ | No log | 3.7941 | 258 | 0.5335 | 0.7366 | 0.5344 |
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+ | No log | 3.8235 | 260 | 0.5399 | 0.7376 | 0.5408 |
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+ | No log | 3.8529 | 262 | 0.5274 | 0.7340 | 0.5282 |
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+ | No log | 3.8824 | 264 | 0.5032 | 0.7390 | 0.5038 |
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+ | No log | 3.9118 | 266 | 0.4953 | 0.7384 | 0.4959 |
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+ | No log | 3.9412 | 268 | 0.4773 | 0.7166 | 0.4778 |
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+ | No log | 3.9706 | 270 | 0.4604 | 0.6906 | 0.4606 |
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+ | No log | 4.0 | 272 | 0.4522 | 0.6585 | 0.4522 |
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+ | No log | 4.0294 | 274 | 0.4498 | 0.6320 | 0.4496 |
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+ | No log | 4.0588 | 276 | 0.4497 | 0.6302 | 0.4495 |
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+ | No log | 4.0882 | 278 | 0.4505 | 0.6510 | 0.4505 |
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+ | No log | 4.1176 | 280 | 0.4585 | 0.6828 | 0.4587 |
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+ | No log | 4.1471 | 282 | 0.4639 | 0.7015 | 0.4642 |
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+ | No log | 4.1765 | 284 | 0.4732 | 0.7132 | 0.4736 |
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+ | No log | 4.2059 | 286 | 0.4774 | 0.7175 | 0.4779 |
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+ | No log | 4.2353 | 288 | 0.4798 | 0.7146 | 0.4803 |
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+ | No log | 4.2647 | 290 | 0.4810 | 0.7175 | 0.4815 |
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+ | No log | 4.2941 | 292 | 0.4834 | 0.7221 | 0.4839 |
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+ | No log | 4.3235 | 294 | 0.4784 | 0.7176 | 0.4788 |
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+ | No log | 4.3529 | 296 | 0.4714 | 0.7062 | 0.4716 |
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+ | No log | 4.3824 | 298 | 0.4744 | 0.7067 | 0.4746 |
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+ | No log | 4.4118 | 300 | 0.4792 | 0.7170 | 0.4795 |
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+ | No log | 4.4412 | 302 | 0.4930 | 0.7249 | 0.4935 |
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+ | No log | 4.4706 | 304 | 0.5034 | 0.7251 | 0.5040 |
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+ | No log | 4.5 | 306 | 0.5084 | 0.7256 | 0.5090 |
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+ | No log | 4.5294 | 308 | 0.5080 | 0.7267 | 0.5086 |
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+ | No log | 4.5588 | 310 | 0.5111 | 0.7258 | 0.5118 |
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+ | No log | 4.5882 | 312 | 0.5187 | 0.7255 | 0.5194 |
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+ | No log | 4.6176 | 314 | 0.5135 | 0.7264 | 0.5142 |
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+ | No log | 4.6471 | 316 | 0.5003 | 0.7254 | 0.5008 |
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+ | No log | 4.6765 | 318 | 0.4859 | 0.7234 | 0.4863 |
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+ | No log | 4.7059 | 320 | 0.4757 | 0.7153 | 0.4760 |
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+ | No log | 4.7353 | 322 | 0.4726 | 0.7002 | 0.4728 |
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+ | No log | 4.7647 | 324 | 0.4722 | 0.6968 | 0.4723 |
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+ | No log | 4.7941 | 326 | 0.4733 | 0.7044 | 0.4735 |
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+ | No log | 4.8235 | 328 | 0.4753 | 0.7082 | 0.4755 |
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+ | No log | 4.8529 | 330 | 0.4782 | 0.7132 | 0.4785 |
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+ | No log | 4.8824 | 332 | 0.4805 | 0.7138 | 0.4808 |
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+ | No log | 4.9118 | 334 | 0.4836 | 0.7103 | 0.4839 |
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+ | No log | 4.9412 | 336 | 0.4856 | 0.7126 | 0.4860 |
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+ | No log | 4.9706 | 338 | 0.4865 | 0.7126 | 0.4869 |
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+ | No log | 5.0 | 340 | 0.4870 | 0.7160 | 0.4874 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
config.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "_name_or_path": "google-bert/bert-base-cased",
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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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+ "gradient_checkpointing": false,
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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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+ "intermediate_size": 3072,
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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": "4.42.3",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 28996
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+ }
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