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rtdetr_v2_r101vd-rocks-finetune-v2

Object Detection
Transformers
Safetensors
rt_detr_v2
Generated from Trainer
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: PekingU/rtdetr_v2_r101vd
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: rtdetr_v2_r101vd-rocks-finetune-v2
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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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+ # rtdetr_v2_r101vd-rocks-finetune-v2
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+
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+ This model is a fine-tuned version of [PekingU/rtdetr_v2_r101vd](https://huggingface.co/PekingU/rtdetr_v2_r101vd) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 13.8126
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+ - Map: 0.0778
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+ - Map 50: 0.1306
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+ - Map 75: 0.0815
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+ - Map Small: 0.1747
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+ - Map Medium: 0.0256
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+ - Map Large: 0.0545
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+ - Mar 1: 0.0779
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+ - Mar 10: 0.4257
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+ - Mar 100: 0.6528
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+ - Mar Small: 0.7518
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+ - Mar Medium: 0.6119
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+ - Mar Large: 0.5793
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+ - Map Stone: 0.0778
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+ - Mar 100 Stone: 0.6528
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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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+ - lr_scheduler_warmup_steps: 300
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+ - num_epochs: 45
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Stone | Mar 100 Stone |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:---------:|:-------------:|
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+ | No log | 1.0 | 130 | 35.1168 | 0.015 | 0.0226 | 0.0139 | 0.0028 | 0.0199 | 0.0286 | 0.0284 | 0.1541 | 0.4076 | 0.2136 | 0.4921 | 0.5467 | 0.015 | 0.4076 |
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+ | No log | 2.0 | 260 | 14.4312 | 0.0872 | 0.1134 | 0.0976 | 0.0398 | 0.1362 | 0.1233 | 0.1479 | 0.3198 | 0.6182 | 0.6264 | 0.6149 | 0.612 | 0.0872 | 0.6182 |
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+ | No log | 3.0 | 390 | 13.4471 | 0.0547 | 0.0805 | 0.0592 | 0.1214 | 0.0833 | 0.0867 | 0.1624 | 0.4571 | 0.6353 | 0.69 | 0.5941 | 0.6152 | 0.0547 | 0.6353 |
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+ | 76.7976 | 4.0 | 520 | 13.5991 | 0.0822 | 0.1127 | 0.0944 | 0.1412 | 0.0524 | 0.0884 | 0.138 | 0.3776 | 0.6172 | 0.6236 | 0.598 | 0.6304 | 0.0822 | 0.6172 |
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+ | 76.7976 | 5.0 | 650 | 13.3898 | 0.1097 | 0.1535 | 0.1234 | 0.1128 | 0.1347 | 0.1324 | 0.168 | 0.463 | 0.6452 | 0.6909 | 0.599 | 0.6413 | 0.1097 | 0.6452 |
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+ | 76.7976 | 6.0 | 780 | 13.1340 | 0.0717 | 0.1261 | 0.0716 | 0.1425 | 0.0682 | 0.0516 | 0.1248 | 0.4508 | 0.6568 | 0.7291 | 0.6238 | 0.6065 | 0.0717 | 0.6568 |
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+ | 76.7976 | 7.0 | 910 | 12.9490 | 0.2071 | 0.291 | 0.234 | 0.287 | 0.1801 | 0.1864 | 0.2277 | 0.5172 | 0.6845 | 0.7627 | 0.6545 | 0.6239 | 0.2071 | 0.6845 |
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+ | 12.8837 | 8.0 | 1040 | 12.5279 | 0.1599 | 0.2268 | 0.1824 | 0.2326 | 0.2017 | 0.0982 | 0.2587 | 0.5376 | 0.6776 | 0.7509 | 0.6426 | 0.6283 | 0.1599 | 0.6776 |
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+ | 12.8837 | 9.0 | 1170 | 13.4474 | 0.1331 | 0.1816 | 0.1557 | 0.1736 | 0.1427 | 0.1336 | 0.2188 | 0.404 | 0.635 | 0.6455 | 0.6168 | 0.6424 | 0.1331 | 0.635 |
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+ | 12.8837 | 10.0 | 1300 | 13.7030 | 0.0635 | 0.093 | 0.0707 | 0.0412 | 0.0593 | 0.1091 | 0.2109 | 0.5013 | 0.6627 | 0.7227 | 0.6337 | 0.6228 | 0.0635 | 0.6627 |
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+ | 12.8837 | 11.0 | 1430 | 13.8766 | 0.0704 | 0.1093 | 0.0733 | 0.0553 | 0.1341 | 0.0605 | 0.1472 | 0.3875 | 0.6271 | 0.6436 | 0.598 | 0.6391 | 0.0704 | 0.6271 |
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+ | 11.6626 | 12.0 | 1560 | 13.3897 | 0.0427 | 0.0696 | 0.0417 | 0.0378 | 0.0619 | 0.0489 | 0.0772 | 0.3914 | 0.6574 | 0.71 | 0.6634 | 0.588 | 0.0427 | 0.6574 |
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+ | 11.6626 | 13.0 | 1690 | 14.1957 | 0.0578 | 0.0996 | 0.0602 | 0.0636 | 0.0867 | 0.0612 | 0.1208 | 0.398 | 0.6366 | 0.6891 | 0.6178 | 0.5946 | 0.0578 | 0.6366 |
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+ | 11.6626 | 14.0 | 1820 | 13.7179 | 0.0742 | 0.1214 | 0.0814 | 0.0803 | 0.0753 | 0.0858 | 0.129 | 0.436 | 0.6512 | 0.6873 | 0.6455 | 0.6141 | 0.0742 | 0.6512 |
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+ | 11.6626 | 15.0 | 1950 | 13.8026 | 0.0429 | 0.0658 | 0.0458 | 0.0304 | 0.0542 | 0.0661 | 0.0611 | 0.3112 | 0.6439 | 0.6664 | 0.6287 | 0.6337 | 0.0429 | 0.6439 |
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+ | 11.0324 | 16.0 | 2080 | 13.1572 | 0.0556 | 0.0905 | 0.0608 | 0.096 | 0.055 | 0.0375 | 0.0983 | 0.3993 | 0.6644 | 0.72 | 0.6554 | 0.6076 | 0.0556 | 0.6644 |
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+ | 11.0324 | 17.0 | 2210 | 13.4430 | 0.087 | 0.135 | 0.0987 | 0.1319 | 0.1137 | 0.0471 | 0.1158 | 0.4756 | 0.667 | 0.7291 | 0.6366 | 0.6261 | 0.087 | 0.667 |
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+ | 11.0324 | 18.0 | 2340 | 13.4700 | 0.0657 | 0.104 | 0.0718 | 0.0804 | 0.0721 | 0.0695 | 0.1234 | 0.4607 | 0.6842 | 0.7409 | 0.6812 | 0.6196 | 0.0657 | 0.6842 |
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+ | 11.0324 | 19.0 | 2470 | 13.6274 | 0.0795 | 0.1324 | 0.0834 | 0.1533 | 0.065 | 0.0367 | 0.097 | 0.4224 | 0.6597 | 0.7482 | 0.5931 | 0.6272 | 0.0795 | 0.6597 |
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+ | 10.2907 | 20.0 | 2600 | 13.5939 | 0.0694 | 0.1102 | 0.0749 | 0.0908 | 0.0537 | 0.1191 | 0.1139 | 0.4479 | 0.6703 | 0.7536 | 0.6228 | 0.6228 | 0.0694 | 0.6703 |
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+ | 10.2907 | 21.0 | 2730 | 13.6512 | 0.1602 | 0.2484 | 0.1792 | 0.2837 | 0.1085 | 0.0816 | 0.165 | 0.4835 | 0.6746 | 0.7591 | 0.6297 | 0.6228 | 0.1602 | 0.6746 |
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+ | 10.2907 | 22.0 | 2860 | 13.7632 | 0.0989 | 0.1648 | 0.105 | 0.1129 | 0.0888 | 0.1174 | 0.1389 | 0.4957 | 0.6713 | 0.7455 | 0.6396 | 0.6174 | 0.0989 | 0.6713 |
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+ | 10.2907 | 23.0 | 2990 | 13.7319 | 0.0991 | 0.1591 | 0.1094 | 0.1326 | 0.0837 | 0.1179 | 0.1284 | 0.4898 | 0.6611 | 0.7391 | 0.6277 | 0.6043 | 0.0991 | 0.6611 |
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+ | 9.5651 | 24.0 | 3120 | 13.4980 | 0.1384 | 0.2217 | 0.1554 | 0.2358 | 0.0747 | 0.1166 | 0.1604 | 0.4795 | 0.6479 | 0.7218 | 0.5891 | 0.6239 | 0.1384 | 0.6479 |
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+ | 9.5651 | 25.0 | 3250 | 13.8530 | 0.0719 | 0.1144 | 0.0773 | 0.1138 | 0.0466 | 0.0917 | 0.1149 | 0.434 | 0.6584 | 0.7236 | 0.6079 | 0.6359 | 0.0719 | 0.6584 |
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+ | 9.5651 | 26.0 | 3380 | 13.2451 | 0.1325 | 0.2041 | 0.1476 | 0.1991 | 0.1156 | 0.0888 | 0.1677 | 0.4937 | 0.6802 | 0.7345 | 0.6713 | 0.625 | 0.1325 | 0.6802 |
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+ | 9.1381 | 27.0 | 3510 | 13.2538 | 0.1073 | 0.166 | 0.1169 | 0.1485 | 0.0674 | 0.1174 | 0.1168 | 0.4779 | 0.6911 | 0.7473 | 0.6683 | 0.6489 | 0.1073 | 0.6911 |
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+ | 9.1381 | 28.0 | 3640 | 13.4400 | 0.147 | 0.2254 | 0.1658 | 0.2306 | 0.096 | 0.1331 | 0.1518 | 0.464 | 0.666 | 0.7273 | 0.6238 | 0.6391 | 0.147 | 0.666 |
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+ | 9.1381 | 29.0 | 3770 | 13.1811 | 0.1424 | 0.2225 | 0.16 | 0.2159 | 0.1288 | 0.1122 | 0.195 | 0.5238 | 0.6785 | 0.7364 | 0.6584 | 0.6315 | 0.1424 | 0.6785 |
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+ | 9.1381 | 30.0 | 3900 | 13.7082 | 0.0969 | 0.154 | 0.11 | 0.1469 | 0.0552 | 0.1168 | 0.1172 | 0.4482 | 0.6502 | 0.7282 | 0.5792 | 0.6348 | 0.0969 | 0.6502 |
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+ | 8.5415 | 31.0 | 4030 | 13.5830 | 0.0852 | 0.1381 | 0.0889 | 0.1253 | 0.0604 | 0.0837 | 0.1208 | 0.4719 | 0.6716 | 0.7564 | 0.6317 | 0.6141 | 0.0852 | 0.6716 |
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+ | 8.5415 | 32.0 | 4160 | 13.8031 | 0.103 | 0.1627 | 0.112 | 0.2026 | 0.0374 | 0.0739 | 0.1221 | 0.4178 | 0.6426 | 0.7291 | 0.5703 | 0.6185 | 0.103 | 0.6426 |
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+ | 8.5415 | 33.0 | 4290 | 13.5155 | 0.1191 | 0.1761 | 0.1371 | 0.2224 | 0.0442 | 0.0714 | 0.1284 | 0.4548 | 0.6538 | 0.74 | 0.5911 | 0.6196 | 0.1191 | 0.6538 |
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+ | 8.5415 | 34.0 | 4420 | 13.8074 | 0.1021 | 0.1633 | 0.1162 | 0.239 | 0.0284 | 0.0499 | 0.098 | 0.4059 | 0.6409 | 0.7327 | 0.5832 | 0.5946 | 0.1021 | 0.6409 |
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+ | 7.9946 | 35.0 | 4550 | 13.4351 | 0.1142 | 0.1809 | 0.1265 | 0.2546 | 0.0512 | 0.0363 | 0.1158 | 0.4142 | 0.6614 | 0.7391 | 0.6178 | 0.6163 | 0.1142 | 0.6614 |
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+ | 7.9946 | 36.0 | 4680 | 13.6085 | 0.1043 | 0.1702 | 0.1139 | 0.2192 | 0.039 | 0.0545 | 0.1033 | 0.4224 | 0.6462 | 0.7391 | 0.602 | 0.5837 | 0.1043 | 0.6462 |
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+ | 7.9946 | 37.0 | 4810 | 13.3631 | 0.1143 | 0.1855 | 0.1271 | 0.2465 | 0.043 | 0.0444 | 0.1007 | 0.4495 | 0.6594 | 0.7591 | 0.6267 | 0.5761 | 0.1143 | 0.6594 |
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+ | 7.9946 | 38.0 | 4940 | 13.6238 | 0.0929 | 0.1545 | 0.1068 | 0.1868 | 0.0373 | 0.0507 | 0.1 | 0.4257 | 0.6561 | 0.7455 | 0.597 | 0.6141 | 0.0929 | 0.6561 |
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+ | 7.4624 | 39.0 | 5070 | 13.6244 | 0.0973 | 0.1638 | 0.1023 | 0.2038 | 0.0294 | 0.0522 | 0.1096 | 0.4083 | 0.6597 | 0.7473 | 0.6139 | 0.6054 | 0.0973 | 0.6597 |
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+ | 7.4624 | 40.0 | 5200 | 13.6516 | 0.0785 | 0.1362 | 0.0857 | 0.1616 | 0.0326 | 0.0424 | 0.0838 | 0.4069 | 0.6538 | 0.7527 | 0.599 | 0.5957 | 0.0785 | 0.6538 |
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+ | 7.4624 | 41.0 | 5330 | 13.7606 | 0.0816 | 0.135 | 0.0881 | 0.1792 | 0.0289 | 0.0404 | 0.0884 | 0.4201 | 0.6594 | 0.7582 | 0.603 | 0.6033 | 0.0816 | 0.6594 |
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+ | 7.4624 | 42.0 | 5460 | 13.7622 | 0.0791 | 0.1306 | 0.0821 | 0.1939 | 0.0239 | 0.0399 | 0.0881 | 0.4007 | 0.6485 | 0.7536 | 0.602 | 0.5739 | 0.0791 | 0.6485 |
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+ | 7.0573 | 43.0 | 5590 | 13.8585 | 0.0758 | 0.1291 | 0.0783 | 0.1804 | 0.026 | 0.0452 | 0.0809 | 0.3911 | 0.6376 | 0.7473 | 0.5842 | 0.5652 | 0.0758 | 0.6376 |
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+ | 7.0573 | 44.0 | 5720 | 13.8280 | 0.0884 | 0.1437 | 0.0965 | 0.1997 | 0.0265 | 0.0564 | 0.0911 | 0.4158 | 0.6548 | 0.7473 | 0.6178 | 0.587 | 0.0884 | 0.6548 |
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+ | 7.0573 | 45.0 | 5850 | 13.8126 | 0.0778 | 0.1306 | 0.0815 | 0.1747 | 0.0256 | 0.0545 | 0.0779 | 0.4257 | 0.6528 | 0.7518 | 0.6119 | 0.5793 | 0.0778 | 0.6528 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.52.0.dev0
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.5.0
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+ - Tokenizers 0.21.1
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