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ihsanahakiim
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videomae-base-finetuned-signlanguage

Video Classification
Transformers
TensorBoard
Safetensors
videomae
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
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  1. README.md +216 -0
  2. model.safetensors +1 -1
  3. runs/Mar02_13-42-27_GAN-SVR/events.out.tfevents.1740890575.GAN-SVR.50119.1 +2 -2
  4. runs/Mar02_13-42-27_GAN-SVR/events.out.tfevents.1740896524.GAN-SVR.50119.2 +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: cc-by-nc-4.0
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+ base_model: MCG-NJU/videomae-base
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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: videomae-base-finetuned-signlanguage
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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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+ # videomae-base-finetuned-signlanguage
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+
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+ This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.3358
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+ - Accuracy: 0.6567
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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: 1e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - training_steps: 3560
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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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+ | 4.2372 | 0.0065 | 23 | 4.2439 | 0.0186 |
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+ | 4.2325 | 1.0065 | 46 | 4.2369 | 0.0186 |
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+ | 4.1795 | 2.0065 | 69 | 4.2250 | 0.0233 |
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+ | 4.211 | 3.0065 | 92 | 4.2141 | 0.0140 |
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+ | 4.2361 | 4.0065 | 115 | 4.2051 | 0.0372 |
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+ | 4.2524 | 5.0065 | 138 | 4.2052 | 0.0233 |
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+ | 4.2297 | 6.0065 | 161 | 4.2014 | 0.0186 |
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+ | 4.2596 | 7.0065 | 184 | 4.1950 | 0.0233 |
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+ | 4.1911 | 8.0065 | 207 | 4.1898 | 0.0326 |
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+ | 4.184 | 9.0065 | 230 | 4.1860 | 0.0279 |
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+ | 4.1731 | 10.0065 | 253 | 4.1680 | 0.0419 |
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+ | 4.098 | 11.0065 | 276 | 4.1413 | 0.0512 |
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+ | 4.1105 | 12.0065 | 299 | 4.1351 | 0.0279 |
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+ | 4.1477 | 13.0065 | 322 | 4.1182 | 0.0372 |
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+ | 4.0121 | 14.0065 | 345 | 4.0324 | 0.0605 |
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+ | 3.8587 | 15.0065 | 368 | 3.9973 | 0.0512 |
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+ | 3.8878 | 16.0065 | 391 | 3.9077 | 0.0651 |
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+ | 3.7205 | 17.0065 | 414 | 3.8901 | 0.0698 |
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+ | 3.6613 | 18.0065 | 437 | 3.7347 | 0.1349 |
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+ | 3.5438 | 19.0065 | 460 | 3.6275 | 0.1488 |
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+ | 3.4033 | 20.0065 | 483 | 3.5495 | 0.1442 |
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+ | 3.2043 | 21.0065 | 506 | 3.5864 | 0.1349 |
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+ | 3.1477 | 22.0065 | 529 | 3.4515 | 0.1674 |
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+ | 3.0344 | 23.0065 | 552 | 3.3110 | 0.2233 |
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+ | 2.9459 | 24.0065 | 575 | 3.2645 | 0.2605 |
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+ | 2.6629 | 25.0065 | 598 | 3.1746 | 0.2558 |
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+ | 2.764 | 26.0065 | 621 | 3.0833 | 0.3163 |
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+ | 2.4924 | 27.0065 | 644 | 2.9918 | 0.3023 |
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+ | 2.6696 | 28.0065 | 667 | 3.0009 | 0.3349 |
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+ | 2.4616 | 29.0065 | 690 | 2.8396 | 0.4 |
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+ | 2.2084 | 30.0065 | 713 | 2.8039 | 0.3674 |
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+ | 2.3011 | 31.0065 | 736 | 2.7465 | 0.4 |
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+ | 2.1059 | 32.0065 | 759 | 2.6865 | 0.4140 |
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+ | 2.0525 | 33.0065 | 782 | 2.6070 | 0.4326 |
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+ | 2.1054 | 34.0065 | 805 | 2.6387 | 0.3953 |
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+ | 1.8791 | 35.0065 | 828 | 2.5539 | 0.4326 |
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+ | 1.7834 | 36.0065 | 851 | 2.4750 | 0.4326 |
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+ | 1.5749 | 37.0065 | 874 | 2.4880 | 0.4233 |
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+ | 1.6162 | 38.0065 | 897 | 2.3581 | 0.4884 |
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+ | 1.5611 | 39.0065 | 920 | 2.2846 | 0.5256 |
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+ | 1.5449 | 40.0065 | 943 | 2.2999 | 0.5116 |
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+ | 1.6013 | 41.0065 | 966 | 2.2349 | 0.5302 |
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+ | 1.3959 | 42.0065 | 989 | 2.1957 | 0.5488 |
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+ | 1.1607 | 43.0065 | 1012 | 2.1559 | 0.5209 |
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+ | 1.2663 | 44.0065 | 1035 | 2.1192 | 0.5721 |
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+ | 1.0869 | 45.0065 | 1058 | 2.0522 | 0.5535 |
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+ | 1.2477 | 46.0065 | 1081 | 2.0597 | 0.5767 |
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+ | 0.9665 | 47.0065 | 1104 | 2.0365 | 0.5535 |
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+ | 1.0521 | 48.0065 | 1127 | 1.9669 | 0.5767 |
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+ | 0.8273 | 49.0065 | 1150 | 1.9918 | 0.5907 |
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+ | 0.8396 | 50.0065 | 1173 | 1.9576 | 0.5860 |
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+ | 0.9543 | 51.0065 | 1196 | 1.9371 | 0.5953 |
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+ | 0.8095 | 52.0065 | 1219 | 1.8800 | 0.5953 |
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+ | 0.7694 | 53.0065 | 1242 | 1.8737 | 0.6 |
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+ | 0.8243 | 54.0065 | 1265 | 1.8846 | 0.6093 |
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+ | 0.6632 | 55.0065 | 1288 | 1.8230 | 0.6 |
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+ | 0.7446 | 56.0065 | 1311 | 1.7898 | 0.6093 |
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+ | 0.7044 | 57.0065 | 1334 | 1.7740 | 0.5907 |
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+ | 0.6732 | 58.0065 | 1357 | 1.8061 | 0.6047 |
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+ | 0.5786 | 59.0065 | 1380 | 1.7060 | 0.6186 |
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+ | 0.6348 | 60.0065 | 1403 | 1.7004 | 0.6140 |
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+ | 0.5706 | 61.0065 | 1426 | 1.7013 | 0.6279 |
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+ | 0.5007 | 62.0065 | 1449 | 1.6992 | 0.6186 |
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+ | 0.5078 | 63.0065 | 1472 | 1.6649 | 0.6047 |
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+ | 0.5048 | 64.0065 | 1495 | 1.6449 | 0.6140 |
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+ | 0.4526 | 65.0065 | 1518 | 1.6256 | 0.6279 |
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+ | 0.504 | 66.0065 | 1541 | 1.6401 | 0.6372 |
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+ | 0.3824 | 67.0065 | 1564 | 1.5941 | 0.6093 |
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+ | 0.453 | 68.0065 | 1587 | 1.6236 | 0.6186 |
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+ | 0.3618 | 69.0065 | 1610 | 1.6100 | 0.6186 |
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+ | 0.3689 | 70.0065 | 1633 | 1.5488 | 0.6419 |
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+ | 0.3545 | 71.0065 | 1656 | 1.5390 | 0.6465 |
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+ | 0.4126 | 72.0065 | 1679 | 1.5287 | 0.6558 |
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+ | 0.2734 | 73.0065 | 1702 | 1.4978 | 0.6465 |
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+ | 0.3144 | 74.0065 | 1725 | 1.5038 | 0.6326 |
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+ | 0.3152 | 75.0065 | 1748 | 1.5692 | 0.6326 |
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+ | 0.371 | 76.0065 | 1771 | 1.5331 | 0.6558 |
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+ | 0.3033 | 77.0065 | 1794 | 1.4733 | 0.6465 |
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+ | 0.2574 | 78.0065 | 1817 | 1.5694 | 0.5907 |
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+ | 0.2562 | 79.0065 | 1840 | 1.5097 | 0.6279 |
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+ | 0.2162 | 80.0065 | 1863 | 1.4782 | 0.6512 |
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+ | 0.2493 | 81.0065 | 1886 | 1.4350 | 0.6465 |
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+ | 0.2173 | 82.0065 | 1909 | 1.4730 | 0.6093 |
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+ | 0.1434 | 98.0065 | 2277 | 1.4055 | 0.6279 |
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+ | 0.1748 | 99.0065 | 2300 | 1.3894 | 0.6558 |
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+ | 0.1007 | 107.0065 | 2484 | 1.3040 | 0.6465 |
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+ | 0.1036 | 108.0065 | 2507 | 1.3216 | 0.6698 |
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+ | 0.1085 | 109.0065 | 2530 | 1.2975 | 0.6326 |
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+ | 0.1231 | 111.0065 | 2576 | 1.3251 | 0.6372 |
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+ | 0.0801 | 112.0065 | 2599 | 1.3120 | 0.6605 |
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+ | 0.1068 | 117.0065 | 2714 | 1.3186 | 0.6744 |
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+ | 0.1507 | 121.0065 | 2806 | 1.3406 | 0.6605 |
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+ | 0.0602 | 122.0065 | 2829 | 1.3187 | 0.6558 |
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+ | 0.0915 | 125.0065 | 2898 | 1.2869 | 0.6465 |
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+ | 0.0665 | 131.0065 | 3036 | 1.2910 | 0.6698 |
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+ | 0.0562 | 132.0065 | 3059 | 1.2820 | 0.6558 |
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+ | 0.0527 | 133.0065 | 3082 | 1.2927 | 0.6651 |
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+ | 0.057 | 134.0065 | 3105 | 1.2846 | 0.6558 |
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+ | 0.0617 | 149.0065 | 3450 | 1.2629 | 0.6605 |
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+ | 0.0525 | 154.0051 | 3560 | 1.2777 | 0.6512 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 3.3.2
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+ - Tokenizers 0.21.0
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