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AleRothermel
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mi-1.2-model

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  1. README.md +184 -0
  2. model.safetensors +1 -1
  3. runs/May20_02-37-11_07b71be6d35e/events.out.tfevents.1716172642.07b71be6d35e.6471.0 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: bert-base-cased
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: mi-1.2-model
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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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+ # mi-1.2-model
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+
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+ This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.7264
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+ - Accuracy: 0.58
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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: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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 | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 1.6501 | 0.04 | 10 | 1.6095 | 0.235 |
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+ | 1.655 | 0.08 | 20 | 1.5876 | 0.23 |
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+ | 1.6465 | 0.12 | 30 | 1.5874 | 0.305 |
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+ | 1.6577 | 0.16 | 40 | 1.6006 | 0.2325 |
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+ | 1.5666 | 0.2 | 50 | 1.5611 | 0.245 |
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+ | 1.5667 | 0.24 | 60 | 1.4245 | 0.44 |
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+ | 1.4837 | 0.28 | 70 | 1.2916 | 0.4175 |
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+ | 1.2603 | 0.32 | 80 | 1.3869 | 0.3925 |
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+ | 1.2865 | 0.36 | 90 | 1.4055 | 0.3475 |
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+ | 1.4037 | 0.4 | 100 | 1.3934 | 0.32 |
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+ | 1.3201 | 0.44 | 110 | 1.4511 | 0.4125 |
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+ | 1.3977 | 0.48 | 120 | 1.2251 | 0.44 |
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+ | 1.1444 | 0.52 | 130 | 1.1517 | 0.5175 |
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+ | 1.1627 | 0.56 | 140 | 1.1211 | 0.5225 |
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+ | 1.21 | 0.6 | 150 | 1.1336 | 0.53 |
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+ | 1.2211 | 0.64 | 160 | 1.4186 | 0.4 |
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+ | 1.2985 | 0.68 | 170 | 1.1251 | 0.4725 |
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+ | 1.1856 | 0.72 | 180 | 1.1138 | 0.5075 |
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+ | 1.1027 | 0.76 | 190 | 1.0810 | 0.5075 |
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+ | 1.0998 | 0.8 | 200 | 1.1034 | 0.5225 |
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+ | 1.2546 | 0.84 | 210 | 1.1205 | 0.4925 |
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+ | 1.0265 | 0.88 | 220 | 1.1996 | 0.4925 |
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+ | 1.0898 | 0.92 | 230 | 1.1002 | 0.515 |
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+ | 1.19 | 0.96 | 240 | 1.0805 | 0.4925 |
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+ | 1.1456 | 1.0 | 250 | 1.0509 | 0.525 |
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+ | 0.9265 | 1.04 | 260 | 1.1092 | 0.51 |
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+ | 0.8554 | 1.08 | 270 | 1.0098 | 0.5325 |
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+ | 0.8695 | 1.12 | 280 | 1.0991 | 0.4975 |
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+ | 0.8505 | 1.16 | 290 | 1.0827 | 0.5075 |
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+ | 0.8892 | 1.2 | 300 | 1.1195 | 0.52 |
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+ | 0.8982 | 1.24 | 310 | 1.0691 | 0.51 |
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+ | 0.9301 | 1.28 | 320 | 1.0236 | 0.545 |
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+ | 1.052 | 1.32 | 330 | 1.0296 | 0.535 |
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+ | 0.8072 | 1.3600 | 340 | 1.0227 | 0.55 |
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+ | 0.8822 | 1.4 | 350 | 1.0494 | 0.53 |
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+ | 1.1561 | 1.44 | 360 | 1.2036 | 0.4925 |
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+ | 0.9526 | 1.48 | 370 | 1.0443 | 0.56 |
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+ | 0.9916 | 1.52 | 380 | 1.0378 | 0.555 |
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+ | 1.0388 | 1.56 | 390 | 1.0920 | 0.5375 |
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+ | 0.9326 | 1.6 | 400 | 1.0510 | 0.5375 |
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+ | 0.8453 | 1.6400 | 410 | 1.1247 | 0.5025 |
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+ | 1.03 | 1.6800 | 420 | 1.0281 | 0.565 |
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+ | 0.971 | 1.72 | 430 | 1.0322 | 0.54 |
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+ | 0.941 | 1.76 | 440 | 0.9858 | 0.565 |
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+ | 0.8615 | 1.8 | 450 | 0.9793 | 0.555 |
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+ | 0.8815 | 1.8400 | 460 | 0.9778 | 0.56 |
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+ | 0.7658 | 1.88 | 470 | 0.9760 | 0.56 |
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+ | 1.0073 | 1.92 | 480 | 1.0747 | 0.5175 |
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+ | 0.8929 | 1.96 | 490 | 0.9910 | 0.565 |
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+ | 0.9089 | 2.0 | 500 | 1.0512 | 0.535 |
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+ | 0.5102 | 2.04 | 510 | 1.0545 | 0.555 |
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+ | 0.6748 | 2.08 | 520 | 1.1621 | 0.5175 |
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+ | 0.5222 | 2.12 | 530 | 1.1038 | 0.5575 |
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+ | 0.7978 | 2.16 | 540 | 1.1728 | 0.53 |
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+ | 0.6749 | 2.2 | 550 | 1.1029 | 0.5475 |
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+ | 0.6621 | 2.24 | 560 | 1.0977 | 0.5425 |
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+ | 0.6808 | 2.2800 | 570 | 1.1776 | 0.545 |
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+ | 0.5728 | 2.32 | 580 | 1.1747 | 0.5325 |
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+ | 0.75 | 2.36 | 590 | 1.1707 | 0.5275 |
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+ | 0.6622 | 2.4 | 600 | 1.1082 | 0.555 |
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+ | 0.6008 | 2.44 | 610 | 1.0922 | 0.57 |
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+ | 0.6491 | 2.48 | 620 | 1.1375 | 0.545 |
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+ | 0.5876 | 2.52 | 630 | 1.0614 | 0.5675 |
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+ | 0.5326 | 2.56 | 640 | 1.0460 | 0.58 |
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+ | 0.4901 | 2.6 | 650 | 1.0864 | 0.58 |
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+ | 0.6151 | 2.64 | 660 | 1.1919 | 0.58 |
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+ | 0.6478 | 2.68 | 670 | 1.1301 | 0.5575 |
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+ | 0.4841 | 2.7200 | 680 | 1.1451 | 0.58 |
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+ | 0.6365 | 2.76 | 690 | 1.0701 | 0.575 |
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+ | 0.5284 | 2.8 | 700 | 1.1674 | 0.5325 |
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+ | 0.6506 | 2.84 | 710 | 1.1016 | 0.55 |
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+ | 0.6446 | 2.88 | 720 | 1.1340 | 0.57 |
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+ | 0.5193 | 2.92 | 730 | 1.1692 | 0.525 |
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+ | 0.6129 | 2.96 | 740 | 1.1717 | 0.5325 |
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+ | 0.6013 | 3.0 | 750 | 1.1374 | 0.55 |
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+ | 0.3392 | 3.04 | 760 | 1.2702 | 0.515 |
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+ | 0.3188 | 3.08 | 770 | 1.2584 | 0.515 |
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+ | 0.3272 | 3.12 | 780 | 1.3520 | 0.5225 |
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+ | 0.341 | 3.16 | 790 | 1.2752 | 0.5575 |
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+ | 0.3826 | 3.2 | 800 | 1.3126 | 0.55 |
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+ | 0.3062 | 3.24 | 810 | 1.4909 | 0.52 |
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+ | 0.2657 | 3.2800 | 820 | 1.3804 | 0.5575 |
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+ | 0.4609 | 3.32 | 830 | 1.3712 | 0.5625 |
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+ | 0.3388 | 3.36 | 840 | 1.4701 | 0.5275 |
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+ | 0.3007 | 3.4 | 850 | 1.3373 | 0.57 |
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+ | 0.2732 | 3.44 | 860 | 1.3699 | 0.575 |
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+ | 0.4551 | 3.48 | 870 | 1.3874 | 0.555 |
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+ | 0.3048 | 3.52 | 880 | 1.4913 | 0.5625 |
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+ | 0.4104 | 3.56 | 890 | 1.4586 | 0.565 |
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+ | 0.2633 | 3.6 | 900 | 1.4353 | 0.565 |
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+ | 0.4435 | 3.64 | 910 | 1.5246 | 0.555 |
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+ | 0.282 | 3.68 | 920 | 1.6866 | 0.5275 |
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+ | 0.5918 | 3.7200 | 930 | 1.5193 | 0.5525 |
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+ | 0.315 | 3.76 | 940 | 1.4276 | 0.565 |
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+ | 0.1276 | 3.8 | 950 | 1.4411 | 0.5625 |
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+ | 0.3389 | 3.84 | 960 | 1.5420 | 0.5625 |
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+ | 0.3248 | 3.88 | 970 | 1.4492 | 0.575 |
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+ | 0.3051 | 3.92 | 980 | 1.4321 | 0.5925 |
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+ | 0.3363 | 3.96 | 990 | 1.4374 | 0.5825 |
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+ | 0.4602 | 4.0 | 1000 | 1.4581 | 0.57 |
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+ | 0.1582 | 4.04 | 1010 | 1.4434 | 0.5675 |
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+ | 0.2344 | 4.08 | 1020 | 1.4551 | 0.5975 |
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+ | 0.2646 | 4.12 | 1030 | 1.4999 | 0.59 |
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+ | 0.1948 | 4.16 | 1040 | 1.5550 | 0.5625 |
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+ | 0.3058 | 4.2 | 1050 | 1.5955 | 0.5775 |
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+ | 0.1569 | 4.24 | 1060 | 1.5721 | 0.575 |
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+ | 0.1777 | 4.28 | 1070 | 1.6241 | 0.56 |
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+ | 0.1256 | 4.32 | 1080 | 1.5711 | 0.575 |
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+ | 0.2467 | 4.36 | 1090 | 1.5735 | 0.59 |
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+ | 0.1964 | 4.4 | 1100 | 1.5924 | 0.585 |
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+ | 0.0578 | 4.44 | 1110 | 1.6353 | 0.585 |
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+ | 0.1358 | 4.48 | 1120 | 1.6710 | 0.5775 |
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+ | 0.174 | 4.52 | 1130 | 1.6733 | 0.5725 |
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+ | 0.2022 | 4.5600 | 1140 | 1.6658 | 0.585 |
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+ | 0.028 | 4.6 | 1150 | 1.6708 | 0.585 |
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+ | 0.1222 | 4.64 | 1160 | 1.6989 | 0.5875 |
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+ | 0.2295 | 4.68 | 1170 | 1.7131 | 0.5825 |
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+ | 0.374 | 4.72 | 1180 | 1.7197 | 0.5725 |
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+ | 0.1342 | 4.76 | 1190 | 1.7237 | 0.575 |
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+ | 0.079 | 4.8 | 1200 | 1.7267 | 0.58 |
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+ | 0.154 | 4.84 | 1210 | 1.7204 | 0.585 |
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+ | 0.0403 | 4.88 | 1220 | 1.7183 | 0.58 |
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+ | 0.1964 | 4.92 | 1230 | 1.7253 | 0.5775 |
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+ | 0.1297 | 4.96 | 1240 | 1.7252 | 0.5775 |
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+ | 0.0834 | 5.0 | 1250 | 1.7264 | 0.58 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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