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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_language_task3_fold3 |
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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_language_task3_fold3 |
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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: 0.3641 |
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- Qwk: 0.6679 |
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- Mse: 0.3649 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
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| No log | 0.0308 | 2 | 0.8306 | 0.1251 | 0.8302 | |
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| No log | 0.0615 | 4 | 0.6714 | 0.0129 | 0.6712 | |
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| No log | 0.0923 | 6 | 0.5734 | 0.0099 | 0.5733 | |
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| No log | 0.1231 | 8 | 0.5391 | 0.0 | 0.5393 | |
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| No log | 0.1538 | 10 | 0.5546 | 0.0 | 0.5548 | |
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| No log | 0.1846 | 12 | 0.5052 | 0.0 | 0.5056 | |
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| No log | 0.2154 | 14 | 0.4823 | 0.0099 | 0.4826 | |
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| No log | 0.2462 | 16 | 0.4737 | 0.0785 | 0.4741 | |
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| No log | 0.2769 | 18 | 0.4572 | 0.2068 | 0.4577 | |
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| No log | 0.3077 | 20 | 0.4337 | 0.3354 | 0.4342 | |
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| No log | 0.3385 | 22 | 0.4440 | 0.4915 | 0.4447 | |
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| No log | 0.3692 | 24 | 0.4478 | 0.5378 | 0.4486 | |
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| No log | 0.4 | 26 | 0.4114 | 0.5344 | 0.4120 | |
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| No log | 0.4308 | 28 | 0.3993 | 0.4289 | 0.3999 | |
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| No log | 0.4615 | 30 | 0.4059 | 0.3404 | 0.4062 | |
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| No log | 0.4923 | 32 | 0.3825 | 0.4644 | 0.3830 | |
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| No log | 0.5231 | 34 | 0.5125 | 0.6055 | 0.5136 | |
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| No log | 0.5538 | 36 | 0.5777 | 0.6026 | 0.5791 | |
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| No log | 0.5846 | 38 | 0.5047 | 0.6024 | 0.5059 | |
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| No log | 0.6154 | 40 | 0.3807 | 0.5499 | 0.3814 | |
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| No log | 0.6462 | 42 | 0.3562 | 0.5243 | 0.3567 | |
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| No log | 0.6769 | 44 | 0.3538 | 0.5252 | 0.3543 | |
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| No log | 0.7077 | 46 | 0.3781 | 0.5832 | 0.3789 | |
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| No log | 0.7385 | 48 | 0.4093 | 0.6070 | 0.4102 | |
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| No log | 0.7692 | 50 | 0.4201 | 0.6186 | 0.4211 | |
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| No log | 0.8 | 52 | 0.3967 | 0.6138 | 0.3976 | |
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| No log | 0.8308 | 54 | 0.3672 | 0.6082 | 0.3679 | |
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| No log | 0.8615 | 56 | 0.3377 | 0.5356 | 0.3381 | |
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| No log | 0.8923 | 58 | 0.3798 | 0.3861 | 0.3797 | |
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| No log | 0.9231 | 60 | 0.3843 | 0.3592 | 0.3841 | |
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| No log | 0.9538 | 62 | 0.3314 | 0.4222 | 0.3316 | |
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| No log | 0.9846 | 64 | 0.3160 | 0.5263 | 0.3165 | |
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| No log | 1.0154 | 66 | 0.3763 | 0.6104 | 0.3773 | |
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| No log | 1.0462 | 68 | 0.4321 | 0.6350 | 0.4332 | |
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| No log | 1.0769 | 70 | 0.3996 | 0.6316 | 0.4007 | |
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| No log | 1.1077 | 72 | 0.3290 | 0.5336 | 0.3297 | |
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| No log | 1.1385 | 74 | 0.3185 | 0.4143 | 0.3188 | |
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| No log | 1.1692 | 76 | 0.3147 | 0.4391 | 0.3150 | |
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| No log | 1.2 | 78 | 0.3078 | 0.5279 | 0.3083 | |
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| No log | 1.2308 | 80 | 0.3069 | 0.5593 | 0.3075 | |
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| No log | 1.2615 | 82 | 0.3144 | 0.5810 | 0.3151 | |
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| No log | 1.2923 | 84 | 0.3365 | 0.6023 | 0.3373 | |
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| No log | 1.3231 | 86 | 0.3249 | 0.5561 | 0.3255 | |
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| No log | 1.3538 | 88 | 0.3339 | 0.4817 | 0.3342 | |
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| No log | 1.3846 | 90 | 0.3238 | 0.5266 | 0.3242 | |
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| No log | 1.4154 | 92 | 0.3559 | 0.6035 | 0.3569 | |
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| No log | 1.4462 | 94 | 0.4087 | 0.6601 | 0.4100 | |
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| No log | 1.4769 | 96 | 0.4345 | 0.6539 | 0.4359 | |
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| No log | 1.5077 | 98 | 0.4370 | 0.6555 | 0.4384 | |
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| No log | 1.5385 | 100 | 0.3598 | 0.6397 | 0.3609 | |
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| No log | 1.5692 | 102 | 0.3039 | 0.5583 | 0.3044 | |
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| No log | 1.6 | 104 | 0.2976 | 0.5335 | 0.2980 | |
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| No log | 1.6308 | 106 | 0.3030 | 0.5666 | 0.3036 | |
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| No log | 1.6615 | 108 | 0.3040 | 0.5691 | 0.3046 | |
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| No log | 1.6923 | 110 | 0.3130 | 0.5853 | 0.3137 | |
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| No log | 1.7231 | 112 | 0.3382 | 0.6151 | 0.3391 | |
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| No log | 1.7538 | 114 | 0.3543 | 0.6348 | 0.3554 | |
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| No log | 1.7846 | 116 | 0.3649 | 0.6422 | 0.3660 | |
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| No log | 1.8154 | 118 | 0.3698 | 0.6487 | 0.3709 | |
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| No log | 1.8462 | 120 | 0.3528 | 0.6447 | 0.3538 | |
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| No log | 1.8769 | 122 | 0.3751 | 0.6637 | 0.3762 | |
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| No log | 1.9077 | 124 | 0.3971 | 0.6610 | 0.3983 | |
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| No log | 1.9385 | 126 | 0.3565 | 0.6653 | 0.3575 | |
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| No log | 1.9692 | 128 | 0.3034 | 0.5766 | 0.3040 | |
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| No log | 2.0 | 130 | 0.2948 | 0.5480 | 0.2954 | |
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| No log | 2.0308 | 132 | 0.3070 | 0.5827 | 0.3077 | |
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| No log | 2.0615 | 134 | 0.3637 | 0.6566 | 0.3647 | |
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| No log | 2.0923 | 136 | 0.4103 | 0.6631 | 0.4115 | |
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| No log | 2.1231 | 138 | 0.4045 | 0.6643 | 0.4057 | |
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| No log | 2.1538 | 140 | 0.3552 | 0.6667 | 0.3561 | |
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| No log | 2.1846 | 142 | 0.3109 | 0.5513 | 0.3113 | |
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| No log | 2.2154 | 144 | 0.3670 | 0.4582 | 0.3669 | |
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| No log | 2.2462 | 146 | 0.3712 | 0.4662 | 0.3711 | |
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| No log | 2.2769 | 148 | 0.3292 | 0.5312 | 0.3295 | |
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| No log | 2.3077 | 150 | 0.3480 | 0.6310 | 0.3488 | |
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| No log | 2.3385 | 152 | 0.3888 | 0.6526 | 0.3900 | |
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| No log | 2.3692 | 154 | 0.4500 | 0.6605 | 0.4514 | |
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| No log | 2.4 | 156 | 0.4250 | 0.6620 | 0.4263 | |
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| No log | 2.4308 | 158 | 0.3710 | 0.6552 | 0.3720 | |
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| No log | 2.4615 | 160 | 0.3132 | 0.6115 | 0.3138 | |
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| No log | 2.4923 | 162 | 0.2975 | 0.5737 | 0.2980 | |
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| No log | 2.5231 | 164 | 0.2938 | 0.5846 | 0.2944 | |
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| No log | 2.5538 | 166 | 0.3015 | 0.6116 | 0.3022 | |
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| No log | 2.5846 | 168 | 0.3224 | 0.6264 | 0.3231 | |
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| No log | 2.6154 | 170 | 0.3834 | 0.6689 | 0.3845 | |
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| No log | 2.6462 | 172 | 0.4118 | 0.6639 | 0.4130 | |
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| No log | 2.6769 | 174 | 0.3792 | 0.6745 | 0.3802 | |
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| No log | 2.7077 | 176 | 0.3231 | 0.6318 | 0.3239 | |
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| No log | 2.7385 | 178 | 0.2894 | 0.5780 | 0.2898 | |
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| No log | 2.7692 | 180 | 0.2889 | 0.5501 | 0.2892 | |
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| No log | 2.8 | 182 | 0.3062 | 0.6314 | 0.3068 | |
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| No log | 2.8308 | 184 | 0.3842 | 0.6697 | 0.3852 | |
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| No log | 2.8615 | 186 | 0.4438 | 0.6625 | 0.4451 | |
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| No log | 2.8923 | 188 | 0.4239 | 0.6741 | 0.4251 | |
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| No log | 2.9231 | 190 | 0.3771 | 0.6622 | 0.3782 | |
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| No log | 2.9538 | 192 | 0.3535 | 0.6459 | 0.3544 | |
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| No log | 2.9846 | 194 | 0.3286 | 0.6182 | 0.3293 | |
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| No log | 3.0154 | 196 | 0.3348 | 0.6233 | 0.3356 | |
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| No log | 3.0462 | 198 | 0.3786 | 0.6738 | 0.3796 | |
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| No log | 3.0769 | 200 | 0.4293 | 0.6788 | 0.4306 | |
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| No log | 3.1077 | 202 | 0.4096 | 0.6720 | 0.4108 | |
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| No log | 3.1385 | 204 | 0.3490 | 0.6591 | 0.3498 | |
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| No log | 3.1692 | 206 | 0.3197 | 0.6380 | 0.3203 | |
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| No log | 3.2 | 208 | 0.3003 | 0.5838 | 0.3007 | |
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| No log | 3.2308 | 210 | 0.2955 | 0.5548 | 0.2959 | |
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| No log | 3.2615 | 212 | 0.2989 | 0.5682 | 0.2994 | |
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| No log | 3.2923 | 214 | 0.3209 | 0.6273 | 0.3215 | |
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| No log | 3.3231 | 216 | 0.3816 | 0.6754 | 0.3825 | |
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| No log | 3.3538 | 218 | 0.4800 | 0.6771 | 0.4813 | |
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| No log | 3.3846 | 220 | 0.5092 | 0.6806 | 0.5106 | |
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| No log | 3.4154 | 222 | 0.4528 | 0.6903 | 0.4539 | |
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| No log | 3.4462 | 224 | 0.3572 | 0.6482 | 0.3579 | |
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| No log | 3.4769 | 226 | 0.3218 | 0.6212 | 0.3223 | |
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| No log | 3.5077 | 228 | 0.3252 | 0.6340 | 0.3257 | |
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| No log | 3.5385 | 230 | 0.3529 | 0.6686 | 0.3537 | |
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| No log | 3.5692 | 232 | 0.4101 | 0.6885 | 0.4112 | |
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| No log | 3.6 | 234 | 0.4086 | 0.6840 | 0.4096 | |
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| No log | 3.6308 | 236 | 0.3599 | 0.6712 | 0.3607 | |
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| No log | 3.6615 | 238 | 0.3240 | 0.6440 | 0.3246 | |
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| No log | 3.6923 | 240 | 0.3211 | 0.6373 | 0.3217 | |
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| No log | 3.7231 | 242 | 0.3433 | 0.6565 | 0.3440 | |
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| No log | 3.7538 | 244 | 0.3885 | 0.6755 | 0.3895 | |
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| No log | 3.7846 | 246 | 0.4180 | 0.6726 | 0.4191 | |
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| No log | 3.8154 | 248 | 0.4314 | 0.6774 | 0.4326 | |
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| No log | 3.8462 | 250 | 0.4021 | 0.6798 | 0.4031 | |
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| No log | 3.8769 | 252 | 0.3549 | 0.6614 | 0.3557 | |
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| No log | 3.9077 | 254 | 0.3336 | 0.6568 | 0.3343 | |
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| No log | 3.9385 | 256 | 0.3341 | 0.6591 | 0.3348 | |
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| No log | 3.9692 | 258 | 0.3482 | 0.6618 | 0.3489 | |
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| No log | 4.0 | 260 | 0.3594 | 0.6665 | 0.3602 | |
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| No log | 4.0308 | 262 | 0.3616 | 0.6613 | 0.3624 | |
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| No log | 4.0615 | 264 | 0.3774 | 0.6586 | 0.3782 | |
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| No log | 4.0923 | 266 | 0.3964 | 0.6596 | 0.3974 | |
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| No log | 4.1231 | 268 | 0.3869 | 0.6655 | 0.3878 | |
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| No log | 4.1538 | 270 | 0.3862 | 0.6623 | 0.3871 | |
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| No log | 4.1846 | 272 | 0.3721 | 0.6554 | 0.3729 | |
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| No log | 4.2154 | 274 | 0.3661 | 0.6583 | 0.3669 | |
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| No log | 4.2462 | 276 | 0.3606 | 0.6623 | 0.3614 | |
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| No log | 4.2769 | 278 | 0.3679 | 0.6590 | 0.3687 | |
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| No log | 4.3077 | 280 | 0.3805 | 0.6565 | 0.3814 | |
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| No log | 4.3385 | 282 | 0.3757 | 0.6586 | 0.3766 | |
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| No log | 4.3692 | 284 | 0.3656 | 0.6621 | 0.3664 | |
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| No log | 4.4 | 286 | 0.3581 | 0.6565 | 0.3589 | |
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| No log | 4.4308 | 288 | 0.3514 | 0.6586 | 0.3521 | |
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| No log | 4.4615 | 290 | 0.3543 | 0.6602 | 0.3550 | |
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| No log | 4.4923 | 292 | 0.3532 | 0.6565 | 0.3539 | |
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| No log | 4.5231 | 294 | 0.3648 | 0.6648 | 0.3656 | |
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| No log | 4.5538 | 296 | 0.3731 | 0.6710 | 0.3739 | |
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| No log | 4.5846 | 298 | 0.3856 | 0.6712 | 0.3865 | |
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| No log | 4.6154 | 300 | 0.4048 | 0.6726 | 0.4057 | |
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| No log | 4.6462 | 302 | 0.4102 | 0.6772 | 0.4112 | |
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| No log | 4.6769 | 304 | 0.4119 | 0.6803 | 0.4129 | |
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| No log | 4.7077 | 306 | 0.4111 | 0.6811 | 0.4121 | |
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| No log | 4.7385 | 308 | 0.4052 | 0.6735 | 0.4062 | |
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| No log | 4.7692 | 310 | 0.3954 | 0.6753 | 0.3964 | |
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| No log | 4.8 | 312 | 0.3905 | 0.6730 | 0.3914 | |
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| No log | 4.8308 | 314 | 0.3836 | 0.6670 | 0.3845 | |
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| No log | 4.8615 | 316 | 0.3768 | 0.6640 | 0.3777 | |
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| No log | 4.8923 | 318 | 0.3712 | 0.6697 | 0.3721 | |
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| No log | 4.9231 | 320 | 0.3676 | 0.6679 | 0.3684 | |
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| No log | 4.9538 | 322 | 0.3652 | 0.6679 | 0.3660 | |
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| No log | 4.9846 | 324 | 0.3641 | 0.6679 | 0.3649 | |
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### Framework versions |
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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 |
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