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bert_baseline_prompt_adherence_task6_fold0

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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. runs/Aug22_15-01-40_0095ffe889f2/events.out.tfevents.1724338901.0095ffe889f2.25.12 +3 -0
  17. runs/Aug22_15-25-58_0095ffe889f2/events.out.tfevents.1724340359.0095ffe889f2.25.13 +3 -0
  18. runs/Aug22_15-50-16_0095ffe889f2/events.out.tfevents.1724341830.0095ffe889f2.25.14 +3 -0
  19. runs/Aug22_16-14-49_0095ffe889f2/events.out.tfevents.1724343290.0095ffe889f2.25.15 +3 -0
  20. 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_fold4
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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_fold4
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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: 0.4514
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+ - Qwk: 0.7238
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+ - Mse: 0.4520
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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 | 2.2632 | 0.0 | 2.2645 |
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+ | No log | 0.0588 | 4 | 1.8737 | 0.0311 | 1.8748 |
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+ | No log | 0.0882 | 6 | 1.5213 | 0.0053 | 1.5222 |
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+ | No log | 0.1176 | 8 | 1.1250 | 0.0053 | 1.1258 |
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+ | No log | 0.1471 | 10 | 0.9630 | 0.0961 | 0.9638 |
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+ | No log | 0.1765 | 12 | 0.8851 | 0.3509 | 0.8855 |
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+ | No log | 0.2059 | 14 | 0.8607 | 0.3171 | 0.8610 |
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+ | No log | 0.2353 | 16 | 0.9310 | 0.2638 | 0.9312 |
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+ | No log | 0.2647 | 18 | 0.8365 | 0.3188 | 0.8368 |
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+ | No log | 0.2941 | 20 | 0.6803 | 0.3703 | 0.6810 |
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+ | No log | 0.3235 | 22 | 0.7056 | 0.3240 | 0.7062 |
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+ | No log | 0.3529 | 24 | 0.5967 | 0.4642 | 0.5971 |
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+ | No log | 0.3824 | 26 | 0.7076 | 0.5621 | 0.7077 |
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+ | No log | 0.4118 | 28 | 0.6812 | 0.5681 | 0.6813 |
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+ | No log | 0.4412 | 30 | 0.6054 | 0.5437 | 0.6055 |
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+ | No log | 0.4706 | 32 | 0.5816 | 0.4983 | 0.5818 |
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+ | No log | 0.5 | 34 | 0.6368 | 0.5175 | 0.6369 |
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+ | No log | 0.5294 | 36 | 0.6274 | 0.5033 | 0.6275 |
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+ | No log | 0.5588 | 38 | 0.6089 | 0.4906 | 0.6090 |
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+ | No log | 0.5882 | 40 | 0.6061 | 0.4948 | 0.6061 |
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+ | No log | 0.6176 | 42 | 0.5572 | 0.5140 | 0.5571 |
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+ | No log | 0.6471 | 44 | 0.5052 | 0.5661 | 0.5052 |
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+ | No log | 0.6765 | 46 | 0.5490 | 0.4825 | 0.5491 |
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+ | No log | 0.7059 | 48 | 0.5075 | 0.4988 | 0.5076 |
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+ | No log | 0.7353 | 50 | 0.5424 | 0.6827 | 0.5421 |
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+ | No log | 0.7647 | 52 | 0.6059 | 0.6859 | 0.6055 |
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+ | No log | 0.7941 | 54 | 0.5719 | 0.6787 | 0.5715 |
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+ | No log | 0.8235 | 56 | 0.5328 | 0.6636 | 0.5325 |
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+ | No log | 0.8529 | 58 | 0.4743 | 0.5609 | 0.4742 |
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+ | No log | 0.8824 | 60 | 0.5113 | 0.4750 | 0.5113 |
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+ | No log | 0.9118 | 62 | 0.5160 | 0.4777 | 0.5160 |
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+ | No log | 0.9412 | 64 | 0.4625 | 0.5749 | 0.4624 |
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+ | No log | 0.9706 | 66 | 0.5494 | 0.6552 | 0.5491 |
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+ | No log | 1.0 | 68 | 0.5967 | 0.6817 | 0.5963 |
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+ | No log | 1.0294 | 70 | 0.5172 | 0.6636 | 0.5168 |
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+ | No log | 1.0588 | 72 | 0.5104 | 0.6776 | 0.5100 |
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+ | No log | 1.0882 | 74 | 0.5221 | 0.7059 | 0.5217 |
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+ | No log | 1.1176 | 76 | 0.4768 | 0.6805 | 0.4764 |
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+ | No log | 1.1471 | 78 | 0.4669 | 0.6749 | 0.4665 |
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+ | No log | 1.1765 | 80 | 0.4885 | 0.7100 | 0.4882 |
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+ | No log | 1.2059 | 82 | 0.6312 | 0.7172 | 0.6307 |
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+ | No log | 1.2353 | 84 | 0.6556 | 0.7054 | 0.6552 |
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+ | No log | 1.2647 | 86 | 0.5130 | 0.7060 | 0.5128 |
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+ | No log | 1.2941 | 88 | 0.4398 | 0.6048 | 0.4398 |
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+ | No log | 1.3235 | 90 | 0.4840 | 0.5213 | 0.4842 |
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+ | No log | 1.3529 | 92 | 0.4776 | 0.5303 | 0.4779 |
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+ | No log | 1.3824 | 94 | 0.4577 | 0.5735 | 0.4579 |
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+ | No log | 1.4118 | 96 | 0.4905 | 0.6288 | 0.4907 |
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+ | No log | 1.4412 | 98 | 0.5674 | 0.6816 | 0.5675 |
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+ | No log | 1.4706 | 100 | 0.6072 | 0.7033 | 0.6073 |
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+ | No log | 1.5 | 102 | 0.5240 | 0.6830 | 0.5240 |
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+ | No log | 1.5294 | 104 | 0.4524 | 0.6542 | 0.4524 |
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+ | No log | 1.5588 | 106 | 0.4339 | 0.6153 | 0.4340 |
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+ | No log | 1.5882 | 108 | 0.4347 | 0.6609 | 0.4347 |
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+ | No log | 1.6176 | 110 | 0.4493 | 0.6831 | 0.4491 |
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+ | No log | 1.6471 | 112 | 0.4591 | 0.6726 | 0.4589 |
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+ | No log | 1.6765 | 114 | 0.4605 | 0.6545 | 0.4603 |
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+ | No log | 1.7059 | 116 | 0.4746 | 0.6899 | 0.4744 |
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+ | No log | 1.7353 | 118 | 0.5271 | 0.7242 | 0.5268 |
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+ | No log | 1.7647 | 120 | 0.5292 | 0.7201 | 0.5290 |
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+ | No log | 1.7941 | 122 | 0.5046 | 0.7119 | 0.5044 |
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+ | No log | 1.8235 | 124 | 0.4503 | 0.6675 | 0.4502 |
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+ | No log | 1.8529 | 126 | 0.4430 | 0.6378 | 0.4429 |
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+ | No log | 1.8824 | 128 | 0.4433 | 0.6610 | 0.4432 |
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+ | No log | 1.9118 | 130 | 0.4850 | 0.6848 | 0.4849 |
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+ | No log | 1.9412 | 132 | 0.5058 | 0.6657 | 0.5058 |
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+ | No log | 1.9706 | 134 | 0.4656 | 0.6590 | 0.4657 |
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+ | No log | 2.0 | 136 | 0.4422 | 0.6264 | 0.4422 |
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+ | No log | 2.0294 | 138 | 0.4303 | 0.6182 | 0.4304 |
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+ | No log | 2.0588 | 140 | 0.4402 | 0.6549 | 0.4403 |
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+ | No log | 2.0882 | 142 | 0.4844 | 0.6887 | 0.4844 |
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+ | No log | 2.1176 | 144 | 0.4897 | 0.7060 | 0.4896 |
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+ | No log | 2.1471 | 146 | 0.4282 | 0.6882 | 0.4282 |
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+ | No log | 2.1765 | 148 | 0.4225 | 0.5967 | 0.4224 |
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+ | No log | 2.2059 | 150 | 0.4645 | 0.5450 | 0.4644 |
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+ | No log | 2.2353 | 152 | 0.4303 | 0.5751 | 0.4302 |
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+ | No log | 2.2647 | 154 | 0.4089 | 0.6906 | 0.4089 |
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+ | No log | 2.2941 | 156 | 0.5125 | 0.7213 | 0.5124 |
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+ | No log | 2.3235 | 158 | 0.5649 | 0.7220 | 0.5647 |
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+ | No log | 2.3529 | 160 | 0.5742 | 0.7254 | 0.5740 |
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+ | No log | 2.3824 | 162 | 0.5027 | 0.7263 | 0.5026 |
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+ | No log | 2.4118 | 164 | 0.4443 | 0.6808 | 0.4443 |
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+ | No log | 2.4412 | 166 | 0.4310 | 0.6198 | 0.4311 |
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+ | No log | 2.4706 | 168 | 0.4381 | 0.5866 | 0.4382 |
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+ | No log | 2.5 | 170 | 0.4395 | 0.5897 | 0.4396 |
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+ | No log | 2.5294 | 172 | 0.4333 | 0.5881 | 0.4335 |
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+ | No log | 2.5588 | 174 | 0.4318 | 0.6280 | 0.4320 |
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+ | No log | 2.5882 | 176 | 0.4755 | 0.6856 | 0.4758 |
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+ | No log | 2.6176 | 178 | 0.5151 | 0.7121 | 0.5154 |
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+ | No log | 2.6471 | 180 | 0.5085 | 0.7069 | 0.5088 |
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+ | No log | 2.6765 | 182 | 0.4746 | 0.7004 | 0.4750 |
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+ | No log | 2.7059 | 184 | 0.4350 | 0.6794 | 0.4353 |
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+ | No log | 2.7353 | 186 | 0.4238 | 0.6654 | 0.4240 |
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+ | No log | 2.7647 | 188 | 0.4218 | 0.6670 | 0.4220 |
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+ | No log | 2.7941 | 190 | 0.4249 | 0.6354 | 0.4251 |
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+ | No log | 2.8235 | 192 | 0.4186 | 0.6660 | 0.4189 |
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+ | No log | 2.8529 | 194 | 0.4409 | 0.7159 | 0.4412 |
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+ | No log | 2.8824 | 196 | 0.5106 | 0.7351 | 0.5109 |
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+ | No log | 2.9118 | 198 | 0.6363 | 0.7094 | 0.6366 |
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+ | No log | 2.9412 | 200 | 0.6510 | 0.7117 | 0.6512 |
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+ | No log | 2.9706 | 202 | 0.5786 | 0.7271 | 0.5789 |
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+ | No log | 3.0 | 204 | 0.5040 | 0.7247 | 0.5042 |
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+ | No log | 3.0294 | 206 | 0.4341 | 0.7067 | 0.4343 |
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+ | No log | 3.0588 | 208 | 0.4172 | 0.6805 | 0.4174 |
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+ | No log | 3.0882 | 210 | 0.4197 | 0.6599 | 0.4200 |
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+ | No log | 3.1176 | 212 | 0.4338 | 0.6765 | 0.4341 |
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+ | No log | 3.1471 | 214 | 0.4612 | 0.6822 | 0.4615 |
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+ | No log | 3.1765 | 216 | 0.4643 | 0.6979 | 0.4646 |
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+ | No log | 3.2059 | 218 | 0.4665 | 0.7120 | 0.4668 |
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+ | No log | 3.2353 | 220 | 0.4568 | 0.7056 | 0.4572 |
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+ | No log | 3.2647 | 222 | 0.4310 | 0.7028 | 0.4314 |
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+ | No log | 3.2941 | 224 | 0.4167 | 0.7020 | 0.4171 |
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+ | No log | 3.3235 | 226 | 0.4082 | 0.6888 | 0.4086 |
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+ | No log | 3.3529 | 228 | 0.4132 | 0.7026 | 0.4136 |
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+ | No log | 3.3824 | 230 | 0.4223 | 0.6991 | 0.4227 |
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+ | No log | 3.4118 | 232 | 0.4429 | 0.7145 | 0.4434 |
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+ | No log | 3.4412 | 234 | 0.4741 | 0.7216 | 0.4746 |
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+ | No log | 3.4706 | 236 | 0.4679 | 0.7194 | 0.4685 |
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+ | No log | 3.5 | 238 | 0.4368 | 0.7083 | 0.4374 |
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+ | No log | 3.5294 | 240 | 0.4200 | 0.6782 | 0.4206 |
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+ | No log | 3.5588 | 242 | 0.4121 | 0.6400 | 0.4127 |
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+ | No log | 3.5882 | 244 | 0.4150 | 0.6397 | 0.4156 |
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+ | No log | 3.6176 | 246 | 0.4316 | 0.6856 | 0.4323 |
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+ | No log | 3.6471 | 248 | 0.4866 | 0.7113 | 0.4872 |
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+ | No log | 3.6765 | 250 | 0.5449 | 0.7200 | 0.5456 |
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+ | No log | 3.7059 | 252 | 0.5358 | 0.7245 | 0.5364 |
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+ | No log | 3.7353 | 254 | 0.4901 | 0.7335 | 0.4907 |
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+ | No log | 3.7647 | 256 | 0.4360 | 0.7213 | 0.4365 |
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+ | No log | 3.7941 | 258 | 0.4002 | 0.6720 | 0.4007 |
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+ | No log | 3.8235 | 260 | 0.4042 | 0.6152 | 0.4047 |
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+ | No log | 3.8529 | 262 | 0.4137 | 0.5922 | 0.4141 |
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+ | No log | 3.8824 | 264 | 0.4040 | 0.6193 | 0.4044 |
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+ | No log | 3.9118 | 266 | 0.3979 | 0.6628 | 0.3984 |
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+ | No log | 3.9412 | 268 | 0.4272 | 0.7077 | 0.4276 |
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+ | No log | 3.9706 | 270 | 0.5074 | 0.7420 | 0.5079 |
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+ | No log | 4.0 | 272 | 0.5778 | 0.7222 | 0.5783 |
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+ | No log | 4.0294 | 274 | 0.5930 | 0.7168 | 0.5935 |
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+ | No log | 4.0588 | 276 | 0.5601 | 0.7166 | 0.5606 |
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+ | No log | 4.0882 | 278 | 0.5035 | 0.7219 | 0.5040 |
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+ | No log | 4.1176 | 280 | 0.4441 | 0.6970 | 0.4446 |
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+ | No log | 4.1471 | 282 | 0.4087 | 0.6766 | 0.4091 |
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+ | No log | 4.1765 | 284 | 0.4023 | 0.6643 | 0.4027 |
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+ | No log | 4.2059 | 286 | 0.4047 | 0.6254 | 0.4051 |
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+ | No log | 4.2353 | 288 | 0.4049 | 0.6221 | 0.4053 |
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+ | No log | 4.2647 | 290 | 0.4032 | 0.6228 | 0.4036 |
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+ | No log | 4.2941 | 292 | 0.4005 | 0.6475 | 0.4009 |
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+ | No log | 4.3235 | 294 | 0.4041 | 0.6730 | 0.4046 |
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+ | No log | 4.3529 | 296 | 0.4233 | 0.7061 | 0.4237 |
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+ | No log | 4.3824 | 298 | 0.4559 | 0.7175 | 0.4565 |
200
+ | No log | 4.4118 | 300 | 0.4891 | 0.7122 | 0.4896 |
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+ | No log | 4.4412 | 302 | 0.5052 | 0.7061 | 0.5058 |
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+ | No log | 4.4706 | 304 | 0.5053 | 0.7081 | 0.5059 |
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+ | No log | 4.5 | 306 | 0.4921 | 0.7092 | 0.4927 |
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+ | No log | 4.5294 | 308 | 0.4751 | 0.7161 | 0.4757 |
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+ | No log | 4.5588 | 310 | 0.4547 | 0.7129 | 0.4553 |
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+ | No log | 4.5882 | 312 | 0.4430 | 0.7165 | 0.4436 |
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+ | No log | 4.6176 | 314 | 0.4314 | 0.7074 | 0.4320 |
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+ | No log | 4.6471 | 316 | 0.4262 | 0.7070 | 0.4267 |
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+ | No log | 4.6765 | 318 | 0.4229 | 0.7030 | 0.4235 |
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+ | No log | 4.7059 | 320 | 0.4266 | 0.7135 | 0.4272 |
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+ | No log | 4.7353 | 322 | 0.4292 | 0.7128 | 0.4297 |
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+ | No log | 4.7647 | 324 | 0.4355 | 0.7159 | 0.4361 |
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+ | No log | 4.7941 | 326 | 0.4437 | 0.7201 | 0.4443 |
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+ | No log | 4.8235 | 328 | 0.4463 | 0.7240 | 0.4468 |
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+ | No log | 4.8529 | 330 | 0.4490 | 0.7230 | 0.4495 |
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+ | No log | 4.8824 | 332 | 0.4485 | 0.7240 | 0.4490 |
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+ | No log | 4.9118 | 334 | 0.4496 | 0.7230 | 0.4502 |
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+ | No log | 4.9412 | 336 | 0.4516 | 0.7201 | 0.4521 |
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+ | No log | 4.9706 | 338 | 0.4518 | 0.7220 | 0.4524 |
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+ | No log | 5.0 | 340 | 0.4514 | 0.7238 | 0.4520 |
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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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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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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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