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bert_baseline_language_task3_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
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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_task6_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_task6_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: 0.3288
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+ - Qwk: 0.7422
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+ - Mse: 0.3288
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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 | 1.8986 | 0.0 | 1.8986 |
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+ | No log | 0.0588 | 4 | 1.6521 | -0.0342 | 1.6521 |
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+ | No log | 0.0882 | 6 | 1.4500 | 0.0004 | 1.4500 |
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+ | No log | 0.1176 | 8 | 1.1609 | 0.0061 | 1.1609 |
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+ | No log | 0.1471 | 10 | 0.9700 | 0.0061 | 0.9700 |
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+ | No log | 0.1765 | 12 | 0.9097 | 0.0061 | 0.9097 |
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+ | No log | 0.2059 | 14 | 0.8141 | 0.0323 | 0.8141 |
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+ | No log | 0.2353 | 16 | 0.7370 | 0.2445 | 0.7370 |
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+ | No log | 0.2647 | 18 | 0.7044 | 0.2300 | 0.7044 |
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+ | No log | 0.2941 | 20 | 0.6348 | 0.4347 | 0.6348 |
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+ | No log | 0.3235 | 22 | 0.7139 | 0.4023 | 0.7139 |
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+ | No log | 0.3529 | 24 | 0.5634 | 0.3840 | 0.5634 |
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+ | No log | 0.3824 | 26 | 0.6137 | 0.2690 | 0.6137 |
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+ | No log | 0.4118 | 28 | 0.5451 | 0.3540 | 0.5451 |
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+ | No log | 0.4412 | 30 | 0.5289 | 0.3626 | 0.5289 |
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+ | No log | 0.4706 | 32 | 0.5049 | 0.3927 | 0.5049 |
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+ | No log | 0.5 | 34 | 0.5319 | 0.4664 | 0.5319 |
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+ | No log | 0.5294 | 36 | 0.4861 | 0.4888 | 0.4861 |
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+ | No log | 0.5588 | 38 | 0.4563 | 0.4702 | 0.4563 |
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+ | No log | 0.5882 | 40 | 0.4365 | 0.4773 | 0.4365 |
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+ | No log | 0.6176 | 42 | 0.4228 | 0.5355 | 0.4228 |
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+ | No log | 0.6471 | 44 | 0.4593 | 0.6269 | 0.4593 |
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+ | No log | 0.6765 | 46 | 0.4971 | 0.6193 | 0.4971 |
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+ | No log | 0.7059 | 48 | 0.4550 | 0.6090 | 0.4550 |
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+ | No log | 0.7353 | 50 | 0.4086 | 0.5866 | 0.4086 |
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+ | No log | 0.7647 | 52 | 0.4576 | 0.5210 | 0.4576 |
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+ | No log | 0.7941 | 54 | 0.3740 | 0.6309 | 0.3740 |
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+ | No log | 0.8235 | 56 | 0.4147 | 0.6481 | 0.4147 |
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+ | No log | 0.8529 | 58 | 0.4043 | 0.6910 | 0.4043 |
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+ | No log | 0.8824 | 60 | 0.3834 | 0.6801 | 0.3834 |
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+ | No log | 0.9118 | 62 | 0.3837 | 0.6727 | 0.3837 |
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+ | No log | 0.9412 | 64 | 0.3774 | 0.6596 | 0.3774 |
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+ | No log | 0.9706 | 66 | 0.3672 | 0.6468 | 0.3672 |
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+ | No log | 1.0 | 68 | 0.3628 | 0.6605 | 0.3628 |
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+ | No log | 1.0294 | 70 | 0.3592 | 0.6620 | 0.3592 |
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+ | No log | 1.0588 | 72 | 0.3749 | 0.6878 | 0.3749 |
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+ | No log | 1.0882 | 74 | 0.3433 | 0.6583 | 0.3433 |
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+ | No log | 1.1176 | 76 | 0.3362 | 0.6459 | 0.3362 |
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+ | No log | 1.1471 | 78 | 0.3935 | 0.7573 | 0.3935 |
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+ | No log | 1.1765 | 80 | 0.3859 | 0.7253 | 0.3859 |
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+ | No log | 1.2059 | 82 | 0.3883 | 0.5852 | 0.3883 |
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+ | No log | 1.2353 | 84 | 0.4080 | 0.5619 | 0.4080 |
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+ | No log | 1.2647 | 86 | 0.3783 | 0.6390 | 0.3783 |
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+ | No log | 1.2941 | 88 | 0.3614 | 0.6297 | 0.3614 |
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+ | No log | 1.3235 | 90 | 0.3642 | 0.5743 | 0.3642 |
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+ | No log | 1.3529 | 92 | 0.3365 | 0.6430 | 0.3365 |
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+ | No log | 1.3824 | 94 | 0.3616 | 0.6944 | 0.3616 |
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+ | No log | 1.4118 | 96 | 0.3127 | 0.6722 | 0.3127 |
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+ | No log | 1.4412 | 98 | 0.3324 | 0.5823 | 0.3324 |
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+ | No log | 1.4706 | 100 | 0.3257 | 0.5839 | 0.3257 |
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+ | No log | 1.5 | 102 | 0.3090 | 0.6764 | 0.3090 |
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+ | No log | 1.5294 | 104 | 0.3270 | 0.6876 | 0.3270 |
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+ | No log | 1.5588 | 106 | 0.3012 | 0.6604 | 0.3012 |
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+ | No log | 1.5882 | 108 | 0.3020 | 0.6283 | 0.3020 |
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+ | No log | 1.6176 | 110 | 0.3053 | 0.6613 | 0.3053 |
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+ | No log | 1.6471 | 112 | 0.3138 | 0.6820 | 0.3138 |
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+ | No log | 1.6765 | 114 | 0.3054 | 0.6508 | 0.3054 |
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+ | No log | 1.7059 | 116 | 0.3037 | 0.6374 | 0.3037 |
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+ | No log | 1.7353 | 118 | 0.3034 | 0.6757 | 0.3034 |
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+ | No log | 1.7647 | 120 | 0.3735 | 0.7649 | 0.3735 |
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+ | No log | 1.7941 | 122 | 0.4315 | 0.7541 | 0.4315 |
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+ | No log | 1.8235 | 124 | 0.3284 | 0.7141 | 0.3284 |
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+ | No log | 1.8529 | 126 | 0.3009 | 0.6005 | 0.3009 |
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+ | No log | 1.8824 | 128 | 0.3623 | 0.5476 | 0.3623 |
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+ | No log | 1.9118 | 130 | 0.3101 | 0.5868 | 0.3101 |
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+ | No log | 1.9412 | 132 | 0.2816 | 0.6661 | 0.2816 |
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+ | No log | 1.9706 | 134 | 0.3151 | 0.7358 | 0.3151 |
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+ | No log | 2.0 | 136 | 0.3870 | 0.7595 | 0.3870 |
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+ | No log | 2.0294 | 138 | 0.3671 | 0.7561 | 0.3671 |
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+ | No log | 2.0588 | 140 | 0.2936 | 0.6983 | 0.2936 |
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+ | No log | 2.0882 | 142 | 0.3417 | 0.5715 | 0.3417 |
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+ | No log | 2.1176 | 144 | 0.4410 | 0.5009 | 0.4410 |
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+ | No log | 2.1471 | 146 | 0.3744 | 0.5453 | 0.3744 |
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+ | No log | 2.1765 | 148 | 0.2889 | 0.6784 | 0.2889 |
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+ | No log | 2.2059 | 150 | 0.3547 | 0.7635 | 0.3547 |
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+ | No log | 2.2353 | 152 | 0.3716 | 0.7670 | 0.3716 |
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+ | No log | 2.2647 | 154 | 0.3037 | 0.7066 | 0.3037 |
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+ | No log | 2.2941 | 156 | 0.3183 | 0.5996 | 0.3183 |
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+ | No log | 2.3235 | 158 | 0.3423 | 0.5677 | 0.3423 |
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+ | No log | 2.3529 | 160 | 0.3120 | 0.6136 | 0.3120 |
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+ | No log | 2.3824 | 162 | 0.2975 | 0.6584 | 0.2975 |
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+ | No log | 2.4118 | 164 | 0.2992 | 0.7014 | 0.2992 |
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+ | No log | 2.4412 | 166 | 0.3403 | 0.7536 | 0.3403 |
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+ | No log | 2.4706 | 168 | 0.3489 | 0.7571 | 0.3489 |
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+ | No log | 2.5 | 170 | 0.3066 | 0.6941 | 0.3066 |
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+ | No log | 2.5294 | 172 | 0.3322 | 0.5994 | 0.3322 |
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+ | No log | 2.5588 | 174 | 0.3234 | 0.6097 | 0.3234 |
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+ | No log | 2.5882 | 176 | 0.3001 | 0.6872 | 0.3001 |
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+ | No log | 2.6176 | 178 | 0.3131 | 0.7070 | 0.3131 |
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+ | No log | 2.6471 | 180 | 0.3284 | 0.7140 | 0.3284 |
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+ | No log | 2.6765 | 182 | 0.3058 | 0.6744 | 0.3058 |
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+ | No log | 2.7059 | 184 | 0.3025 | 0.6450 | 0.3025 |
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+ | No log | 2.7353 | 186 | 0.3145 | 0.6126 | 0.3145 |
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+ | No log | 2.7647 | 188 | 0.3056 | 0.6316 | 0.3056 |
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+ | No log | 2.7941 | 190 | 0.3063 | 0.6902 | 0.3063 |
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+ | No log | 2.8235 | 192 | 0.3425 | 0.7332 | 0.3425 |
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+ | No log | 2.8529 | 194 | 0.3476 | 0.7439 | 0.3476 |
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+ | No log | 2.8824 | 196 | 0.3112 | 0.7238 | 0.3112 |
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+ | No log | 2.9118 | 198 | 0.3028 | 0.6338 | 0.3028 |
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+ | No log | 2.9412 | 200 | 0.3258 | 0.5995 | 0.3258 |
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+ | No log | 2.9706 | 202 | 0.3027 | 0.6328 | 0.3027 |
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+ | No log | 3.0 | 204 | 0.2961 | 0.7051 | 0.2961 |
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+ | No log | 3.0294 | 206 | 0.3291 | 0.7439 | 0.3291 |
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+ | No log | 3.0588 | 208 | 0.3521 | 0.7631 | 0.3521 |
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+ | No log | 3.0882 | 210 | 0.3390 | 0.7666 | 0.3390 |
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+ | No log | 3.1176 | 212 | 0.2953 | 0.7179 | 0.2953 |
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+ | No log | 3.1471 | 214 | 0.3073 | 0.6244 | 0.3073 |
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+ | No log | 3.1765 | 216 | 0.3247 | 0.5912 | 0.3247 |
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+ | No log | 3.2059 | 218 | 0.3058 | 0.6445 | 0.3058 |
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+ | No log | 3.2353 | 220 | 0.3027 | 0.7135 | 0.3027 |
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+ | No log | 3.2647 | 222 | 0.3270 | 0.7607 | 0.3270 |
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+ | No log | 3.2941 | 224 | 0.3380 | 0.7545 | 0.3380 |
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+ | No log | 3.3235 | 226 | 0.3145 | 0.7426 | 0.3145 |
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+ | No log | 3.3529 | 228 | 0.3005 | 0.7080 | 0.3005 |
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+ | No log | 3.3824 | 230 | 0.2996 | 0.7013 | 0.2996 |
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+ | No log | 3.4118 | 232 | 0.3066 | 0.7205 | 0.3066 |
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+ | No log | 3.4412 | 234 | 0.3115 | 0.7364 | 0.3115 |
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+ | No log | 3.4706 | 236 | 0.3052 | 0.7199 | 0.3052 |
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+ | No log | 3.5 | 238 | 0.2957 | 0.7052 | 0.2957 |
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+ | No log | 3.5294 | 240 | 0.3011 | 0.7119 | 0.3011 |
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+ | No log | 3.5588 | 242 | 0.3020 | 0.7088 | 0.3020 |
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+ | No log | 3.5882 | 244 | 0.3001 | 0.6948 | 0.3001 |
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+ | No log | 3.6176 | 246 | 0.3081 | 0.6610 | 0.3081 |
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+ | No log | 3.6471 | 248 | 0.3126 | 0.6487 | 0.3126 |
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+ | No log | 3.6765 | 250 | 0.3060 | 0.6905 | 0.3060 |
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+ | No log | 3.7059 | 252 | 0.3270 | 0.7420 | 0.3270 |
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+ | No log | 3.7353 | 254 | 0.3838 | 0.7812 | 0.3838 |
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+ | No log | 3.7647 | 256 | 0.3868 | 0.7830 | 0.3868 |
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+ | No log | 3.7941 | 258 | 0.3482 | 0.7628 | 0.3482 |
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+ | No log | 3.8235 | 260 | 0.3310 | 0.7413 | 0.3310 |
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+ | No log | 3.8529 | 262 | 0.3239 | 0.7306 | 0.3239 |
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+ | No log | 3.8824 | 264 | 0.3178 | 0.7226 | 0.3178 |
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+ | No log | 3.9118 | 266 | 0.3097 | 0.7029 | 0.3097 |
184
+ | No log | 3.9412 | 268 | 0.3040 | 0.6942 | 0.3040 |
185
+ | No log | 3.9706 | 270 | 0.3031 | 0.7134 | 0.3031 |
186
+ | No log | 4.0 | 272 | 0.3131 | 0.7232 | 0.3131 |
187
+ | No log | 4.0294 | 274 | 0.3172 | 0.7320 | 0.3172 |
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+ | No log | 4.0588 | 276 | 0.3222 | 0.7423 | 0.3222 |
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+ | No log | 4.0882 | 278 | 0.3102 | 0.7190 | 0.3102 |
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+ | No log | 4.1176 | 280 | 0.3026 | 0.7184 | 0.3026 |
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+ | No log | 4.1471 | 282 | 0.3004 | 0.6990 | 0.3004 |
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+ | No log | 4.1765 | 284 | 0.3016 | 0.6906 | 0.3016 |
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+ | No log | 4.2059 | 286 | 0.3036 | 0.6829 | 0.3036 |
194
+ | No log | 4.2353 | 288 | 0.3067 | 0.7002 | 0.3067 |
195
+ | No log | 4.2647 | 290 | 0.3080 | 0.7033 | 0.3080 |
196
+ | No log | 4.2941 | 292 | 0.3101 | 0.7100 | 0.3101 |
197
+ | No log | 4.3235 | 294 | 0.3092 | 0.7100 | 0.3092 |
198
+ | No log | 4.3529 | 296 | 0.3150 | 0.7207 | 0.3150 |
199
+ | No log | 4.3824 | 298 | 0.3224 | 0.7287 | 0.3224 |
200
+ | No log | 4.4118 | 300 | 0.3194 | 0.7227 | 0.3194 |
201
+ | No log | 4.4412 | 302 | 0.3218 | 0.7287 | 0.3218 |
202
+ | No log | 4.4706 | 304 | 0.3285 | 0.7363 | 0.3285 |
203
+ | No log | 4.5 | 306 | 0.3234 | 0.7321 | 0.3234 |
204
+ | No log | 4.5294 | 308 | 0.3236 | 0.7321 | 0.3236 |
205
+ | No log | 4.5588 | 310 | 0.3237 | 0.7317 | 0.3237 |
206
+ | No log | 4.5882 | 312 | 0.3206 | 0.7262 | 0.3206 |
207
+ | No log | 4.6176 | 314 | 0.3205 | 0.7224 | 0.3205 |
208
+ | No log | 4.6471 | 316 | 0.3246 | 0.7314 | 0.3246 |
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+ | No log | 4.6765 | 318 | 0.3278 | 0.7348 | 0.3278 |
210
+ | No log | 4.7059 | 320 | 0.3285 | 0.7410 | 0.3285 |
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+ | No log | 4.7353 | 322 | 0.3334 | 0.7426 | 0.3334 |
212
+ | No log | 4.7647 | 324 | 0.3351 | 0.7454 | 0.3351 |
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+ | No log | 4.7941 | 326 | 0.3374 | 0.7448 | 0.3374 |
214
+ | No log | 4.8235 | 328 | 0.3390 | 0.7479 | 0.3390 |
215
+ | No log | 4.8529 | 330 | 0.3375 | 0.7459 | 0.3375 |
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+ | No log | 4.8824 | 332 | 0.3364 | 0.7448 | 0.3364 |
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+ | No log | 4.9118 | 334 | 0.3345 | 0.7457 | 0.3345 |
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+ | No log | 4.9412 | 336 | 0.3317 | 0.7457 | 0.3317 |
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+ | No log | 4.9706 | 338 | 0.3294 | 0.7422 | 0.3294 |
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+ | No log | 5.0 | 340 | 0.3288 | 0.7422 | 0.3288 |
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+
222
+
223
+ ### Framework versions
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+
225
+ - 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
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+ {
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+ "_name_or_path": "google-bert/bert-base-cased",
3
+ "architectures": [
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+ "BertForSequenceClassification"
5
+ ],
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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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+ "LABEL_0": 0
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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",
23
+ "num_attention_heads": 12,
24
+ "num_hidden_layers": 12,
25
+ "pad_token_id": 0,
26
+ "position_embedding_type": "absolute",
27
+ "problem_type": "regression",
28
+ "torch_dtype": "float32",
29
+ "transformers_version": "4.42.3",
30
+ "type_vocab_size": 2,
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+ "use_cache": true,
32
+ "vocab_size": 28996
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+ }
model.safetensors ADDED
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