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alem-147
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poisoned-baseline2

Image Classification
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mobilenet_v2
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  1. README.md +159 -0
  2. logs/events.out.tfevents.1733192533.1d6e803c86f2.518.2 +2 -2
  3. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ library_name: transformers
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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: poisoned-baseline2
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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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+ # poisoned-baseline2
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 9.7330
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+ - Accuracy: 0.6466
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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: 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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+ - num_epochs: 100
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+ - mixed_precision_training: Native AMP
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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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+ | 1.1307 | 1.0 | 130 | 1.0262 | 0.4962 |
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+ | 1.0927 | 2.0 | 260 | 1.7590 | 0.2632 |
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+ | 1.0507 | 3.0 | 390 | 2.1327 | 0.5188 |
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+ | 1.0081 | 4.0 | 520 | 1.3239 | 0.5714 |
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+ | 0.9565 | 5.0 | 650 | 1.1102 | 0.5489 |
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+ | 0.7963 | 6.0 | 780 | 1.3624 | 0.6917 |
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+ | 0.6663 | 7.0 | 910 | 5.5153 | 0.5564 |
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+ | 0.6336 | 8.0 | 1040 | 5.0001 | 0.5940 |
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+ | 0.5852 | 9.0 | 1170 | 9.5447 | 0.5489 |
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+ | 0.5467 | 10.0 | 1300 | 6.4452 | 0.5714 |
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+ | 0.5318 | 11.0 | 1430 | 12.3394 | 0.5038 |
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+ | 0.5177 | 12.0 | 1560 | 3.9932 | 0.5940 |
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+ | 0.4431 | 13.0 | 1690 | 1.7703 | 0.6541 |
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+ | 0.4164 | 14.0 | 1820 | 4.0616 | 0.5038 |
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+ | 0.4392 | 15.0 | 1950 | 1.3017 | 0.7744 |
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+ | 0.4356 | 16.0 | 2080 | 1.1080 | 0.7293 |
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+ | 0.3853 | 17.0 | 2210 | 5.3221 | 0.5789 |
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+ | 0.3911 | 18.0 | 2340 | 1.3064 | 0.7143 |
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+ | 0.3493 | 19.0 | 2470 | 8.7354 | 0.5564 |
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+ | 0.3017 | 20.0 | 2600 | 1.4359 | 0.6466 |
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+ | 0.3532 | 21.0 | 2730 | 5.5559 | 0.6241 |
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+ | 0.2868 | 22.0 | 2860 | 3.5486 | 0.5263 |
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+ | 0.3125 | 23.0 | 2990 | 7.4942 | 0.6617 |
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+ | 0.326 | 24.0 | 3120 | 3.8914 | 0.7143 |
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+ | 0.2561 | 25.0 | 3250 | 2.8141 | 0.6692 |
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+ | 0.2923 | 26.0 | 3380 | 6.7704 | 0.6090 |
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+ | 0.2311 | 27.0 | 3510 | 1.8806 | 0.7293 |
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+ | 0.2274 | 28.0 | 3640 | 2.3829 | 0.6316 |
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+ | 0.2481 | 29.0 | 3770 | 3.2873 | 0.5940 |
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+ | 0.2612 | 30.0 | 3900 | 1.7361 | 0.7368 |
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+ | 0.2541 | 31.0 | 4030 | 6.3135 | 0.6241 |
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+ | 0.1998 | 32.0 | 4160 | 4.0907 | 0.6842 |
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+ | 0.2628 | 33.0 | 4290 | 4.6728 | 0.7068 |
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+ | 0.2515 | 34.0 | 4420 | 3.1405 | 0.6617 |
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+ | 0.2352 | 35.0 | 4550 | 3.2859 | 0.7519 |
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+ | 0.242 | 36.0 | 4680 | 0.8856 | 0.7594 |
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+ | 0.2095 | 37.0 | 4810 | 5.4219 | 0.6692 |
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+ | 0.2173 | 38.0 | 4940 | 9.1599 | 0.6842 |
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+ | 0.1865 | 39.0 | 5070 | 2.9133 | 0.7293 |
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+ | 0.2539 | 40.0 | 5200 | 10.3407 | 0.6241 |
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+ | 0.2512 | 41.0 | 5330 | 4.8001 | 0.7218 |
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+ | 0.2304 | 42.0 | 5460 | 8.2643 | 0.6767 |
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+ | 0.1761 | 43.0 | 5590 | 6.4020 | 0.6466 |
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+ | 0.1947 | 44.0 | 5720 | 2.3283 | 0.7293 |
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+ | 0.2011 | 45.0 | 5850 | 3.2135 | 0.6842 |
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+ | 0.1789 | 46.0 | 5980 | 2.5271 | 0.7218 |
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+ | 0.1217 | 47.0 | 6110 | 3.5338 | 0.7218 |
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+ | 0.197 | 48.0 | 6240 | 2.8379 | 0.7669 |
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+ | 0.1378 | 49.0 | 6370 | 6.7036 | 0.6767 |
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+ | 0.1641 | 50.0 | 6500 | 5.3123 | 0.6692 |
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+ | 0.171 | 51.0 | 6630 | 29.0727 | 0.5489 |
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+ | 0.1694 | 52.0 | 6760 | 3.9145 | 0.7669 |
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+ | 0.1694 | 53.0 | 6890 | 20.2058 | 0.6015 |
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+ | 0.0983 | 54.0 | 7020 | 3.0154 | 0.7444 |
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+ | 0.0983 | 55.0 | 7150 | 4.5036 | 0.6992 |
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+ | 0.1116 | 56.0 | 7280 | 15.8594 | 0.5564 |
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+ | 0.1467 | 57.0 | 7410 | 1.9574 | 0.7744 |
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+ | 0.1161 | 58.0 | 7540 | 7.0993 | 0.5940 |
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+ | 0.1424 | 59.0 | 7670 | 5.0006 | 0.7368 |
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+ | 0.0921 | 60.0 | 7800 | 10.6072 | 0.6015 |
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+ | 0.1014 | 61.0 | 7930 | 3.9741 | 0.7368 |
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+ | 0.1456 | 62.0 | 8060 | 2.6188 | 0.7744 |
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+ | 0.2115 | 63.0 | 8190 | 5.3006 | 0.6617 |
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+ | 0.1167 | 64.0 | 8320 | 3.2966 | 0.6992 |
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+ | 0.0746 | 65.0 | 8450 | 2.1400 | 0.7594 |
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+ | 0.0694 | 66.0 | 8580 | 5.7985 | 0.6767 |
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+ | 0.0515 | 67.0 | 8710 | 3.5244 | 0.6767 |
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+ | 0.0513 | 68.0 | 8840 | 4.2358 | 0.6917 |
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+ | 0.1511 | 69.0 | 8970 | 6.8578 | 0.6541 |
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+ | 0.1871 | 70.0 | 9100 | 12.4745 | 0.6617 |
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+ | 0.114 | 71.0 | 9230 | 2.7450 | 0.7594 |
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+ | 0.0438 | 72.0 | 9360 | 5.2159 | 0.6842 |
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+ | 0.054 | 73.0 | 9490 | 3.8337 | 0.7143 |
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+ | 0.1645 | 74.0 | 9620 | 12.4765 | 0.5789 |
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+ | 0.0655 | 75.0 | 9750 | 3.4949 | 0.7143 |
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+ | 0.0676 | 76.0 | 9880 | 3.7470 | 0.7293 |
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+ | 0.1427 | 77.0 | 10010 | 9.8213 | 0.6316 |
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+ | 0.099 | 78.0 | 10140 | 14.3845 | 0.6015 |
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+ | 0.0943 | 79.0 | 10270 | 3.3007 | 0.7895 |
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+ | 0.0971 | 80.0 | 10400 | 4.5807 | 0.6917 |
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+ | 0.1338 | 81.0 | 10530 | 7.8281 | 0.6692 |
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+ | 0.0494 | 82.0 | 10660 | 10.0532 | 0.6617 |
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+ | 0.0384 | 83.0 | 10790 | 3.4354 | 0.7820 |
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+ | 0.0781 | 84.0 | 10920 | 7.8234 | 0.6316 |
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+ | 0.1122 | 85.0 | 11050 | 5.1243 | 0.7068 |
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+ | 0.0965 | 86.0 | 11180 | 7.5119 | 0.6617 |
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+ | 0.1852 | 87.0 | 11310 | 11.2423 | 0.6015 |
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+ | 0.0512 | 88.0 | 11440 | 2.3147 | 0.7744 |
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+ | 0.0456 | 89.0 | 11570 | 2.9752 | 0.7744 |
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+ | 0.0479 | 90.0 | 11700 | 17.1507 | 0.6241 |
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+ | 0.04 | 91.0 | 11830 | 2.8366 | 0.7068 |
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+ | 0.1437 | 92.0 | 11960 | 16.1989 | 0.5789 |
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+ | 0.0256 | 93.0 | 12090 | 3.2687 | 0.6917 |
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+ | 0.0178 | 94.0 | 12220 | 3.8819 | 0.7068 |
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+ | 0.0356 | 95.0 | 12350 | 2.6739 | 0.6992 |
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+ | 0.1282 | 96.0 | 12480 | 8.0099 | 0.6466 |
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+ | 0.0544 | 97.0 | 12610 | 11.1235 | 0.6466 |
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+ | 0.0502 | 98.0 | 12740 | 4.4413 | 0.6241 |
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+ | 0.0398 | 99.0 | 12870 | 26.8311 | 0.5188 |
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+ | 0.1161 | 100.0 | 13000 | 9.7330 | 0.6466 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.3
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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