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rtdetr_v2_r101vd-rocks-finetune

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
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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
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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: 12.1315
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+ - Map: 0.6911
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+ - Map 50: 0.9158
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+ - Map 75: 0.9158
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+ - Map Small: 0.6597
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+ - Map Medium: 0.7
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+ - Map Large: -1.0
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+ - Mar 1: 0.5
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+ - Mar 10: 0.8333
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+ - Mar 100: 0.8333
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+ - Mar Small: 0.9
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+ - Mar Medium: 0.7
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+ - Mar Large: -1.0
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+ - Map Stone: 0.6911
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+ - Mar 100 Stone: 0.8333
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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 | 43.3717 | 0.0276 | 0.0423 | 0.0301 | 0.0336 | 0.0313 | 0.0333 | 0.0416 | 0.4188 | 0.565 | 0.5609 | 0.5564 | 0.5793 | 0.0276 | 0.565 |
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+ | No log | 2.0 | 260 | 19.5303 | 0.199 | 0.2747 | 0.2335 | 0.5123 | 0.228 | 0.0269 | 0.1921 | 0.535 | 0.6119 | 0.6936 | 0.595 | 0.5326 | 0.199 | 0.6119 |
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+ | No log | 3.0 | 390 | 14.1844 | 0.1391 | 0.2029 | 0.1548 | 0.1355 | 0.1813 | 0.1363 | 0.2475 | 0.5729 | 0.6287 | 0.6518 | 0.6228 | 0.6076 | 0.1391 | 0.6287 |
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+ | 76.178 | 4.0 | 520 | 14.1197 | 0.2443 | 0.3365 | 0.2704 | 0.3443 | 0.2898 | 0.1733 | 0.235 | 0.5792 | 0.6264 | 0.6636 | 0.6208 | 0.588 | 0.2443 | 0.6264 |
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+ | 76.178 | 5.0 | 650 | 14.1867 | 0.1413 | 0.1963 | 0.1623 | 0.1773 | 0.1702 | 0.1508 | 0.1389 | 0.5531 | 0.6498 | 0.6909 | 0.6495 | 0.6011 | 0.1413 | 0.6498 |
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+ | 76.178 | 6.0 | 780 | 14.0705 | 0.217 | 0.3 | 0.2459 | 0.3437 | 0.2312 | 0.1259 | 0.1934 | 0.5548 | 0.6488 | 0.6973 | 0.6386 | 0.6022 | 0.217 | 0.6488 |
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+ | 76.178 | 7.0 | 910 | 14.4345 | 0.1072 | 0.164 | 0.1146 | 0.1183 | 0.1408 | 0.1143 | 0.1917 | 0.5472 | 0.665 | 0.7373 | 0.6584 | 0.5859 | 0.1072 | 0.665 |
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+ | 13.1861 | 8.0 | 1040 | 14.1636 | 0.093 | 0.1354 | 0.0994 | 0.1355 | 0.1011 | 0.1415 | 0.1795 | 0.5224 | 0.6439 | 0.6973 | 0.6386 | 0.5859 | 0.093 | 0.6439 |
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+ | 13.1861 | 9.0 | 1170 | 14.2129 | 0.2464 | 0.3366 | 0.2799 | 0.4291 | 0.2459 | 0.0826 | 0.1931 | 0.5677 | 0.6601 | 0.7182 | 0.6347 | 0.6185 | 0.2464 | 0.6601 |
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+ | 13.1861 | 10.0 | 1300 | 14.2845 | 0.3264 | 0.4559 | 0.3618 | 0.518 | 0.3047 | 0.094 | 0.2492 | 0.6033 | 0.6564 | 0.7045 | 0.6436 | 0.613 | 0.3264 | 0.6564 |
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+ | 13.1861 | 11.0 | 1430 | 13.8762 | 0.2687 | 0.3688 | 0.3145 | 0.433 | 0.2836 | 0.1072 | 0.2251 | 0.5627 | 0.6683 | 0.72 | 0.6614 | 0.6141 | 0.2687 | 0.6683 |
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+ | 11.7639 | 12.0 | 1560 | 13.9386 | 0.2306 | 0.3174 | 0.273 | 0.3377 | 0.3147 | 0.13 | 0.232 | 0.5531 | 0.6502 | 0.6982 | 0.6396 | 0.6043 | 0.2306 | 0.6502 |
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+ | 11.7639 | 13.0 | 1690 | 14.2454 | 0.1776 | 0.2663 | 0.1957 | 0.3221 | 0.1609 | 0.0457 | 0.1809 | 0.5211 | 0.6512 | 0.6809 | 0.6554 | 0.6109 | 0.1776 | 0.6512 |
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+ | 11.7639 | 14.0 | 1820 | 14.3947 | 0.2122 | 0.2965 | 0.2381 | 0.3411 | 0.2566 | 0.0955 | 0.2267 | 0.5571 | 0.6531 | 0.7091 | 0.6267 | 0.6152 | 0.2122 | 0.6531 |
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+ | 11.7639 | 15.0 | 1950 | 14.4063 | 0.2711 | 0.3709 | 0.3106 | 0.4107 | 0.307 | 0.1042 | 0.232 | 0.5723 | 0.6482 | 0.7027 | 0.6248 | 0.6087 | 0.2711 | 0.6482 |
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+ | 11.0387 | 16.0 | 2080 | 14.7560 | 0.2464 | 0.3446 | 0.2848 | 0.4027 | 0.2642 | 0.1113 | 0.2073 | 0.5591 | 0.6452 | 0.6955 | 0.6396 | 0.5913 | 0.2464 | 0.6452 |
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+ | 11.0387 | 17.0 | 2210 | 14.3657 | 0.2377 | 0.3213 | 0.2779 | 0.4069 | 0.2185 | 0.0691 | 0.1683 | 0.562 | 0.6776 | 0.7255 | 0.6693 | 0.6293 | 0.2377 | 0.6776 |
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+ | 11.0387 | 18.0 | 2340 | 14.7338 | 0.1282 | 0.1787 | 0.1436 | 0.2257 | 0.0918 | 0.0771 | 0.1571 | 0.5036 | 0.6584 | 0.7091 | 0.6465 | 0.6109 | 0.1282 | 0.6584 |
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+ | 11.0387 | 19.0 | 2470 | 13.8830 | 0.2278 | 0.3285 | 0.2549 | 0.3816 | 0.2429 | 0.0808 | 0.2069 | 0.5726 | 0.665 | 0.7136 | 0.6436 | 0.6304 | 0.2278 | 0.665 |
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+ | 10.3071 | 20.0 | 2600 | 13.9696 | 0.2359 | 0.3283 | 0.2678 | 0.3442 | 0.2589 | 0.2031 | 0.2452 | 0.5931 | 0.6726 | 0.7382 | 0.6475 | 0.6217 | 0.2359 | 0.6726 |
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+ | 10.3071 | 21.0 | 2730 | 14.1270 | 0.2196 | 0.3031 | 0.2525 | 0.3577 | 0.2166 | 0.1295 | 0.2079 | 0.532 | 0.6591 | 0.7309 | 0.6267 | 0.6087 | 0.2196 | 0.6591 |
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+ | 10.3071 | 22.0 | 2860 | 14.3896 | 0.2209 | 0.3264 | 0.2574 | 0.396 | 0.1652 | 0.0887 | 0.1769 | 0.5182 | 0.6459 | 0.7055 | 0.6347 | 0.587 | 0.2209 | 0.6459 |
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+ | 10.3071 | 23.0 | 2990 | 14.4689 | 0.2234 | 0.3249 | 0.2436 | 0.3388 | 0.2667 | 0.071 | 0.2033 | 0.5426 | 0.6624 | 0.7036 | 0.6446 | 0.6326 | 0.2234 | 0.6624 |
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+ | 9.6574 | 24.0 | 3120 | 14.6690 | 0.2165 | 0.2991 | 0.2533 | 0.3543 | 0.225 | 0.0944 | 0.2182 | 0.5482 | 0.6637 | 0.7245 | 0.6455 | 0.6109 | 0.2165 | 0.6637 |
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+ | 9.6574 | 25.0 | 3250 | 14.7214 | 0.2511 | 0.3417 | 0.2827 | 0.4054 | 0.2958 | 0.0878 | 0.2066 | 0.5446 | 0.6469 | 0.7082 | 0.599 | 0.6261 | 0.2511 | 0.6469 |
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+ | 9.6574 | 26.0 | 3380 | 14.4813 | 0.2302 | 0.3265 | 0.2656 | 0.3893 | 0.2184 | 0.1056 | 0.1891 | 0.5162 | 0.6528 | 0.7155 | 0.6158 | 0.6185 | 0.2302 | 0.6528 |
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+ | 9.0433 | 27.0 | 3510 | 14.5406 | 0.2407 | 0.3245 | 0.2803 | 0.3773 | 0.268 | 0.1287 | 0.2076 | 0.5347 | 0.6482 | 0.7145 | 0.6277 | 0.5913 | 0.2407 | 0.6482 |
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+ | 9.0433 | 28.0 | 3640 | 14.4553 | 0.2026 | 0.2886 | 0.2381 | 0.2977 | 0.2368 | 0.0888 | 0.2139 | 0.5396 | 0.6502 | 0.7 | 0.6406 | 0.6011 | 0.2026 | 0.6502 |
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+ | 9.0433 | 29.0 | 3770 | 14.7926 | 0.2045 | 0.2902 | 0.2295 | 0.322 | 0.2166 | 0.0971 | 0.2109 | 0.5172 | 0.6386 | 0.7 | 0.6109 | 0.5957 | 0.2045 | 0.6386 |
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+ | 9.0433 | 30.0 | 3900 | 14.9966 | 0.2289 | 0.3217 | 0.2619 | 0.3852 | 0.243 | 0.0661 | 0.2168 | 0.5083 | 0.6548 | 0.7127 | 0.6515 | 0.5891 | 0.2289 | 0.6548 |
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+ | 8.5206 | 31.0 | 4030 | 14.8464 | 0.2238 | 0.3236 | 0.2494 | 0.3919 | 0.1991 | 0.0635 | 0.1908 | 0.5132 | 0.6419 | 0.7109 | 0.6267 | 0.5761 | 0.2238 | 0.6419 |
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+ | 8.5206 | 32.0 | 4160 | 14.9270 | 0.2427 | 0.3487 | 0.2798 | 0.395 | 0.2652 | 0.0847 | 0.2162 | 0.5182 | 0.632 | 0.7109 | 0.602 | 0.5707 | 0.2427 | 0.632 |
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+ | 8.5206 | 33.0 | 4290 | 14.6849 | 0.2358 | 0.3282 | 0.2763 | 0.3972 | 0.2281 | 0.0893 | 0.2046 | 0.5317 | 0.6521 | 0.7282 | 0.6228 | 0.5935 | 0.2358 | 0.6521 |
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+ | 8.5206 | 34.0 | 4420 | 14.7376 | 0.2675 | 0.3831 | 0.3025 | 0.4577 | 0.238 | 0.087 | 0.2251 | 0.5498 | 0.6495 | 0.7173 | 0.6168 | 0.6043 | 0.2675 | 0.6495 |
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+ | 7.9929 | 35.0 | 4550 | 14.7160 | 0.2474 | 0.3483 | 0.28 | 0.4288 | 0.2226 | 0.0857 | 0.1983 | 0.534 | 0.6455 | 0.7218 | 0.6178 | 0.5848 | 0.2474 | 0.6455 |
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+ | 7.9929 | 36.0 | 4680 | 14.2937 | 0.2556 | 0.3545 | 0.2968 | 0.424 | 0.2496 | 0.1339 | 0.2139 | 0.5469 | 0.6515 | 0.72 | 0.6426 | 0.5793 | 0.2556 | 0.6515 |
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+ | 7.9929 | 37.0 | 4810 | 14.6087 | 0.2737 | 0.3809 | 0.3078 | 0.4279 | 0.268 | 0.1645 | 0.2459 | 0.5558 | 0.6508 | 0.7109 | 0.6208 | 0.612 | 0.2737 | 0.6508 |
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+ | 7.9929 | 38.0 | 4940 | 14.7062 | 0.239 | 0.3428 | 0.2685 | 0.4064 | 0.2152 | 0.0871 | 0.196 | 0.5241 | 0.6337 | 0.7136 | 0.6109 | 0.563 | 0.239 | 0.6337 |
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+ | 7.5722 | 39.0 | 5070 | 14.8826 | 0.252 | 0.3564 | 0.2801 | 0.4203 | 0.2244 | 0.1091 | 0.2145 | 0.5409 | 0.6399 | 0.7145 | 0.6059 | 0.588 | 0.252 | 0.6399 |
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+ | 7.5722 | 40.0 | 5200 | 14.7745 | 0.2677 | 0.3671 | 0.3017 | 0.44 | 0.2654 | 0.1579 | 0.2251 | 0.5505 | 0.6505 | 0.7282 | 0.6218 | 0.5891 | 0.2677 | 0.6505 |
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+ | 7.5722 | 41.0 | 5330 | 14.9496 | 0.2455 | 0.3407 | 0.2728 | 0.4184 | 0.2176 | 0.1036 | 0.2046 | 0.5343 | 0.638 | 0.7245 | 0.5911 | 0.5859 | 0.2455 | 0.638 |
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+ | 7.5722 | 42.0 | 5460 | 15.1104 | 0.2375 | 0.3346 | 0.259 | 0.4124 | 0.2009 | 0.097 | 0.1835 | 0.5191 | 0.6376 | 0.7182 | 0.6158 | 0.5652 | 0.2375 | 0.6376 |
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+ | 7.1411 | 43.0 | 5590 | 15.1514 | 0.2455 | 0.3469 | 0.2643 | 0.4123 | 0.2304 | 0.0974 | 0.2026 | 0.5257 | 0.638 | 0.7118 | 0.6079 | 0.5826 | 0.2455 | 0.638 |
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+ | 7.1411 | 44.0 | 5720 | 15.0940 | 0.2383 | 0.3423 | 0.2613 | 0.3993 | 0.2116 | 0.0984 | 0.199 | 0.5099 | 0.6208 | 0.7018 | 0.5822 | 0.5663 | 0.2383 | 0.6208 |
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+ | 7.1411 | 45.0 | 5850 | 15.0988 | 0.2459 | 0.3522 | 0.2692 | 0.4006 | 0.2335 | 0.1053 | 0.2165 | 0.5191 | 0.6241 | 0.7036 | 0.5842 | 0.5728 | 0.2459 | 0.6241 |
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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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