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  1. README.md +38 -38
  2. runs/Aug22_09-38-15_4a91f28c1eab/events.out.tfevents.1724319507.4a91f28c1eab.34.0 +3 -0
  3. runs/Aug22_09-43-32_4a91f28c1eab/events.out.tfevents.1724319813.4a91f28c1eab.34.1 +3 -0
  4. runs/Aug22_09-48-51_4a91f28c1eab/events.out.tfevents.1724320132.4a91f28c1eab.34.2 +3 -0
  5. runs/Aug22_09-54-11_4a91f28c1eab/events.out.tfevents.1724320452.4a91f28c1eab.34.3 +3 -0
  6. runs/Aug22_09-59-15_4a91f28c1eab/events.out.tfevents.1724320757.4a91f28c1eab.34.4 +3 -0
  7. runs/Aug22_10-04-35_4a91f28c1eab/events.out.tfevents.1724321076.4a91f28c1eab.34.5 +3 -0
  8. runs/Aug22_10-09-58_4a91f28c1eab/events.out.tfevents.1724321399.4a91f28c1eab.34.6 +3 -0
  9. training_args.bin +1 -1
README.md CHANGED
@@ -4,20 +4,20 @@ 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_task4_fold1
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  results: []
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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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- # bert_baseline_prompt_adherence_task4_fold1
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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: 0.3776
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- - Qwk: 0.6594
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- - Mse: 0.3794
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  ## Model description
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@@ -48,39 +48,39 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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- | No log | 0.0299 | 2 | 2.2564 | 0.0 | 2.2575 |
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- | No log | 0.0597 | 4 | 1.6809 | 0.0 | 1.6816 |
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- | No log | 0.0896 | 6 | 1.0910 | 0.0 | 1.0910 |
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- | No log | 0.1194 | 8 | 0.7512 | 0.2651 | 0.7511 |
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- | No log | 0.1493 | 10 | 0.6255 | 0.3428 | 0.6255 |
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- | No log | 0.1791 | 12 | 0.5553 | 0.3646 | 0.5554 |
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- | No log | 0.2090 | 14 | 0.5086 | 0.3601 | 0.5089 |
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- | No log | 0.2388 | 16 | 0.5178 | 0.3566 | 0.5186 |
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- | No log | 0.2687 | 18 | 0.4479 | 0.4269 | 0.4487 |
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- | No log | 0.2985 | 20 | 0.4166 | 0.4397 | 0.4172 |
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- | No log | 0.3284 | 22 | 0.4894 | 0.3973 | 0.4896 |
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- | No log | 0.3582 | 24 | 0.4800 | 0.4089 | 0.4803 |
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- | No log | 0.3881 | 26 | 0.4100 | 0.4996 | 0.4107 |
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- | No log | 0.4179 | 28 | 0.4060 | 0.5607 | 0.4074 |
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- | No log | 0.4478 | 30 | 0.4137 | 0.5350 | 0.4151 |
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- | No log | 0.4776 | 32 | 0.4050 | 0.5391 | 0.4063 |
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- | No log | 0.5075 | 34 | 0.4049 | 0.5581 | 0.4063 |
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- | No log | 0.5373 | 36 | 0.4067 | 0.5113 | 0.4078 |
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- | No log | 0.5672 | 38 | 0.4015 | 0.5240 | 0.4026 |
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- | No log | 0.5970 | 40 | 0.3886 | 0.5907 | 0.3900 |
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- | No log | 0.6269 | 42 | 0.3885 | 0.6312 | 0.3902 |
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- | No log | 0.6567 | 44 | 0.3907 | 0.6442 | 0.3925 |
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- | No log | 0.6866 | 46 | 0.3806 | 0.6424 | 0.3822 |
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- | No log | 0.7164 | 48 | 0.3733 | 0.6378 | 0.3747 |
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- | No log | 0.7463 | 50 | 0.3688 | 0.6029 | 0.3700 |
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- | No log | 0.7761 | 52 | 0.3637 | 0.6021 | 0.3649 |
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- | No log | 0.8060 | 54 | 0.3610 | 0.6445 | 0.3623 |
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- | No log | 0.8358 | 56 | 0.3617 | 0.6492 | 0.3631 |
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- | No log | 0.8657 | 58 | 0.3610 | 0.6441 | 0.3625 |
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- | No log | 0.8955 | 60 | 0.3702 | 0.6499 | 0.3718 |
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- | No log | 0.9254 | 62 | 0.3774 | 0.6599 | 0.3791 |
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- | No log | 0.9552 | 64 | 0.3767 | 0.6599 | 0.3784 |
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- | No log | 0.9851 | 66 | 0.3776 | 0.6594 | 0.3794 |
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  ### Framework versions
 
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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_task4_fold0
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  results: []
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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. -->
13
 
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+ # bert_baseline_prompt_adherence_task4_fold0
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16
  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.
17
  It achieves the following results on the evaluation set:
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+ - Loss: 0.4271
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+ - Qwk: 0.6387
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+ - Mse: 0.4239
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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+ | No log | 0.0299 | 2 | 1.2960 | 0.0 | 1.2930 |
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+ | No log | 0.0597 | 4 | 0.9177 | 0.0 | 0.9154 |
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+ | No log | 0.0896 | 6 | 0.8271 | 0.3838 | 0.8254 |
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+ | No log | 0.1194 | 8 | 0.7326 | 0.3465 | 0.7313 |
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+ | No log | 0.1493 | 10 | 0.6599 | 0.3581 | 0.6586 |
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+ | No log | 0.1791 | 12 | 0.6243 | 0.3717 | 0.6227 |
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+ | No log | 0.2090 | 14 | 0.6024 | 0.3919 | 0.6005 |
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+ | No log | 0.2388 | 16 | 0.5293 | 0.3990 | 0.5275 |
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+ | No log | 0.2687 | 18 | 0.5958 | 0.6599 | 0.5946 |
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+ | No log | 0.2985 | 20 | 0.5865 | 0.6470 | 0.5851 |
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+ | No log | 0.3284 | 22 | 0.4997 | 0.6200 | 0.4975 |
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+ | No log | 0.3582 | 24 | 0.4852 | 0.4550 | 0.4825 |
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+ | No log | 0.3881 | 26 | 0.5626 | 0.3360 | 0.5596 |
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+ | No log | 0.4179 | 28 | 0.6943 | 0.2663 | 0.6911 |
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+ | No log | 0.4478 | 30 | 0.6648 | 0.2753 | 0.6616 |
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+ | No log | 0.4776 | 32 | 0.5340 | 0.3669 | 0.5308 |
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+ | No log | 0.5075 | 34 | 0.4475 | 0.5778 | 0.4444 |
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+ | No log | 0.5373 | 36 | 0.4749 | 0.6546 | 0.4720 |
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+ | No log | 0.5672 | 38 | 0.5331 | 0.6635 | 0.5306 |
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+ | No log | 0.5970 | 40 | 0.5591 | 0.6712 | 0.5569 |
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+ | No log | 0.6269 | 42 | 0.5329 | 0.6517 | 0.5307 |
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+ | No log | 0.6567 | 44 | 0.4773 | 0.6521 | 0.4749 |
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+ | No log | 0.6866 | 46 | 0.4526 | 0.5105 | 0.4499 |
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+ | No log | 0.7164 | 48 | 0.4667 | 0.4248 | 0.4638 |
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+ | No log | 0.7463 | 50 | 0.4597 | 0.4232 | 0.4567 |
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+ | No log | 0.7761 | 52 | 0.4413 | 0.4921 | 0.4382 |
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+ | No log | 0.8060 | 54 | 0.4265 | 0.5327 | 0.4234 |
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+ | No log | 0.8358 | 56 | 0.4218 | 0.5857 | 0.4188 |
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+ | No log | 0.8657 | 58 | 0.4221 | 0.6155 | 0.4191 |
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+ | No log | 0.8955 | 60 | 0.4244 | 0.6239 | 0.4213 |
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+ | No log | 0.9254 | 62 | 0.4273 | 0.6354 | 0.4242 |
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+ | No log | 0.9552 | 64 | 0.4272 | 0.6387 | 0.4241 |
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+ | No log | 0.9851 | 66 | 0.4271 | 0.6387 | 0.4239 |
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  ### Framework versions
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