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dit-base_tobacco-tiny_tobacco3482_kd_CEKD_t2.5_a0.5

Image Classification
Transformers
Safetensors
vit
Generated from Trainer
Inference Endpoints
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  1. README.md +166 -0
  2. config.json +48 -0
  3. model.safetensors +3 -0
  4. test-logits.npz +3 -0
  5. test-references.npz +3 -0
  6. training_args.bin +3 -0
  7. validation-logits.npz +3 -0
  8. validation-references.npz +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: WinKawaks/vit-tiny-patch16-224
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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: dit-base_tobacco-tiny_tobacco3482_kd_CEKD_t2.5_a0.5
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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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+ # dit-base_tobacco-tiny_tobacco3482_kd_CEKD_t2.5_a0.5
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+
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+ This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6206
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+ - Accuracy: 0.825
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+ - Brier Loss: 0.2570
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+ - Nll: 0.9939
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+ - F1 Micro: 0.825
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+ - F1 Macro: 0.8166
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+ - Ece: 0.1370
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+ - Aurc: 0.0444
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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: 0.0001
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 100
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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 | Brier Loss | Nll | F1 Micro | F1 Macro | Ece | Aurc |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:|
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+ | No log | 1.0 | 7 | 4.0511 | 0.22 | 0.9320 | 7.5162 | 0.22 | 0.0792 | 0.3104 | 0.7615 |
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+ | No log | 2.0 | 14 | 3.4353 | 0.35 | 0.8214 | 5.1797 | 0.35 | 0.2316 | 0.2589 | 0.6234 |
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+ | No log | 3.0 | 21 | 2.6406 | 0.47 | 0.6828 | 2.9202 | 0.47 | 0.3725 | 0.2781 | 0.3277 |
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+ | No log | 4.0 | 28 | 2.0027 | 0.57 | 0.5596 | 1.8624 | 0.57 | 0.4971 | 0.2526 | 0.2124 |
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+ | No log | 5.0 | 35 | 1.5018 | 0.65 | 0.4518 | 1.7094 | 0.65 | 0.6128 | 0.2242 | 0.1396 |
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+ | No log | 6.0 | 42 | 1.3904 | 0.71 | 0.4105 | 1.8765 | 0.7100 | 0.7058 | 0.2202 | 0.1126 |
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+ | No log | 7.0 | 49 | 1.1226 | 0.76 | 0.3558 | 1.8024 | 0.76 | 0.7029 | 0.1815 | 0.0841 |
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+ | No log | 8.0 | 56 | 1.1810 | 0.73 | 0.3716 | 1.5642 | 0.7300 | 0.7027 | 0.1956 | 0.0834 |
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+ | No log | 9.0 | 63 | 1.2131 | 0.73 | 0.3811 | 1.7544 | 0.7300 | 0.6774 | 0.2070 | 0.0872 |
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+ | No log | 10.0 | 70 | 1.3986 | 0.72 | 0.4043 | 2.0161 | 0.72 | 0.7259 | 0.2021 | 0.1098 |
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+ | No log | 11.0 | 77 | 1.1001 | 0.765 | 0.3202 | 1.9113 | 0.765 | 0.7578 | 0.1859 | 0.0678 |
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+ | No log | 12.0 | 84 | 1.0429 | 0.77 | 0.3487 | 1.2955 | 0.7700 | 0.7663 | 0.1910 | 0.0827 |
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+ | No log | 13.0 | 91 | 0.9864 | 0.77 | 0.3227 | 1.3721 | 0.7700 | 0.7734 | 0.1692 | 0.0710 |
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+ | No log | 14.0 | 98 | 1.0068 | 0.74 | 0.3581 | 1.3362 | 0.74 | 0.7271 | 0.1848 | 0.0804 |
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+ | No log | 15.0 | 105 | 0.8635 | 0.795 | 0.3009 | 1.4785 | 0.795 | 0.7810 | 0.1646 | 0.0538 |
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+ | No log | 16.0 | 112 | 0.8157 | 0.81 | 0.2845 | 1.2525 | 0.81 | 0.7931 | 0.1545 | 0.0519 |
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+ | No log | 17.0 | 119 | 0.8616 | 0.78 | 0.3186 | 1.4230 | 0.78 | 0.7705 | 0.1610 | 0.0647 |
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+ | No log | 18.0 | 126 | 0.8034 | 0.8 | 0.2784 | 1.4410 | 0.8000 | 0.7811 | 0.1576 | 0.0489 |
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+ | No log | 19.0 | 133 | 0.7601 | 0.805 | 0.2697 | 1.2885 | 0.805 | 0.7823 | 0.1499 | 0.0494 |
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+ | No log | 20.0 | 140 | 0.7598 | 0.82 | 0.2709 | 1.3643 | 0.82 | 0.8090 | 0.1542 | 0.0516 |
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+ | No log | 21.0 | 147 | 0.8221 | 0.79 | 0.2905 | 1.4031 | 0.79 | 0.7640 | 0.1612 | 0.0585 |
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+ | No log | 22.0 | 154 | 0.7271 | 0.825 | 0.2599 | 1.0950 | 0.825 | 0.8147 | 0.1381 | 0.0454 |
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+ | No log | 23.0 | 161 | 0.7556 | 0.795 | 0.2891 | 1.1111 | 0.795 | 0.7822 | 0.1413 | 0.0558 |
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+ | No log | 24.0 | 168 | 0.7197 | 0.81 | 0.2759 | 1.1361 | 0.81 | 0.7905 | 0.1617 | 0.0500 |
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+ | No log | 25.0 | 175 | 0.7192 | 0.83 | 0.2620 | 1.3395 | 0.83 | 0.8155 | 0.1459 | 0.0433 |
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+ | No log | 26.0 | 182 | 0.7347 | 0.805 | 0.2821 | 1.1396 | 0.805 | 0.7868 | 0.1512 | 0.0541 |
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+ | No log | 27.0 | 189 | 0.7402 | 0.815 | 0.2805 | 1.3562 | 0.815 | 0.7928 | 0.1489 | 0.0519 |
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+ | No log | 28.0 | 196 | 0.6986 | 0.815 | 0.2562 | 1.1454 | 0.815 | 0.7944 | 0.1467 | 0.0443 |
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+ | No log | 29.0 | 203 | 0.7148 | 0.81 | 0.2718 | 1.1404 | 0.81 | 0.7944 | 0.1440 | 0.0513 |
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+ | No log | 30.0 | 210 | 0.7041 | 0.81 | 0.2796 | 1.3773 | 0.81 | 0.7998 | 0.1484 | 0.0494 |
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+ | No log | 31.0 | 217 | 0.7428 | 0.815 | 0.2823 | 1.1146 | 0.815 | 0.7967 | 0.1626 | 0.0542 |
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+ | No log | 32.0 | 224 | 0.6941 | 0.82 | 0.2682 | 1.1921 | 0.82 | 0.8098 | 0.1427 | 0.0478 |
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+ | No log | 33.0 | 231 | 0.7170 | 0.81 | 0.2794 | 1.2244 | 0.81 | 0.7875 | 0.1407 | 0.0511 |
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+ | No log | 34.0 | 238 | 0.7024 | 0.815 | 0.2805 | 1.0423 | 0.815 | 0.8043 | 0.1560 | 0.0512 |
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+ | No log | 35.0 | 245 | 0.7299 | 0.81 | 0.2710 | 1.1835 | 0.81 | 0.7964 | 0.1475 | 0.0530 |
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+ | No log | 36.0 | 252 | 0.6488 | 0.83 | 0.2500 | 1.1662 | 0.83 | 0.8117 | 0.1315 | 0.0431 |
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+ | No log | 37.0 | 259 | 0.6877 | 0.815 | 0.2751 | 1.0878 | 0.815 | 0.7973 | 0.1381 | 0.0489 |
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+ | No log | 38.0 | 266 | 0.7019 | 0.84 | 0.2620 | 1.2709 | 0.8400 | 0.8282 | 0.1607 | 0.0498 |
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+ | No log | 39.0 | 273 | 0.6687 | 0.81 | 0.2680 | 1.3004 | 0.81 | 0.7959 | 0.1346 | 0.0465 |
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+ | No log | 40.0 | 280 | 0.6813 | 0.81 | 0.2809 | 1.0539 | 0.81 | 0.7929 | 0.1628 | 0.0500 |
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+ | No log | 41.0 | 287 | 0.6525 | 0.83 | 0.2493 | 1.1496 | 0.83 | 0.8176 | 0.1413 | 0.0437 |
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+ | No log | 42.0 | 294 | 0.6526 | 0.835 | 0.2547 | 1.2429 | 0.835 | 0.8253 | 0.1420 | 0.0450 |
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+ | No log | 43.0 | 301 | 0.6696 | 0.82 | 0.2717 | 1.0446 | 0.82 | 0.8118 | 0.1486 | 0.0501 |
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+ | No log | 44.0 | 308 | 0.6555 | 0.83 | 0.2626 | 0.9948 | 0.83 | 0.8214 | 0.1366 | 0.0461 |
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+ | No log | 45.0 | 315 | 0.6380 | 0.82 | 0.2600 | 1.2151 | 0.82 | 0.8026 | 0.1263 | 0.0428 |
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+ | No log | 46.0 | 322 | 0.6356 | 0.82 | 0.2571 | 1.0923 | 0.82 | 0.8114 | 0.1443 | 0.0449 |
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+ | No log | 47.0 | 329 | 0.6444 | 0.815 | 0.2638 | 1.0657 | 0.815 | 0.7980 | 0.1503 | 0.0476 |
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+ | No log | 48.0 | 336 | 0.6337 | 0.82 | 0.2676 | 1.0650 | 0.82 | 0.8077 | 0.1370 | 0.0442 |
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+ | No log | 49.0 | 343 | 0.6271 | 0.84 | 0.2541 | 1.1500 | 0.8400 | 0.8230 | 0.1365 | 0.0422 |
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+ | No log | 50.0 | 350 | 0.6284 | 0.81 | 0.2588 | 1.2703 | 0.81 | 0.7964 | 0.1411 | 0.0425 |
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+ | No log | 51.0 | 357 | 0.6507 | 0.82 | 0.2612 | 1.1306 | 0.82 | 0.7996 | 0.1558 | 0.0460 |
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+ | No log | 52.0 | 364 | 0.6329 | 0.825 | 0.2602 | 1.2060 | 0.825 | 0.8146 | 0.1296 | 0.0439 |
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+ | No log | 53.0 | 371 | 0.6342 | 0.825 | 0.2574 | 1.0132 | 0.825 | 0.8158 | 0.1467 | 0.0434 |
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+ | No log | 54.0 | 378 | 0.6486 | 0.82 | 0.2633 | 1.1662 | 0.82 | 0.8060 | 0.1445 | 0.0466 |
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+ | No log | 55.0 | 385 | 0.6245 | 0.825 | 0.2588 | 1.1358 | 0.825 | 0.8088 | 0.1428 | 0.0429 |
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+ | No log | 56.0 | 392 | 0.6303 | 0.815 | 0.2616 | 0.9843 | 0.815 | 0.8013 | 0.1447 | 0.0458 |
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+ | No log | 57.0 | 399 | 0.6196 | 0.82 | 0.2545 | 1.1936 | 0.82 | 0.8076 | 0.1516 | 0.0438 |
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+ | No log | 58.0 | 406 | 0.6241 | 0.82 | 0.2620 | 1.0557 | 0.82 | 0.8100 | 0.1423 | 0.0450 |
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+ | No log | 59.0 | 413 | 0.6278 | 0.82 | 0.2579 | 1.0777 | 0.82 | 0.8076 | 0.1382 | 0.0451 |
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+ | No log | 60.0 | 420 | 0.6385 | 0.81 | 0.2651 | 0.9962 | 0.81 | 0.7910 | 0.1565 | 0.0467 |
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+ | No log | 61.0 | 427 | 0.6328 | 0.82 | 0.2619 | 0.9968 | 0.82 | 0.8103 | 0.1299 | 0.0469 |
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+ | No log | 62.0 | 434 | 0.6195 | 0.82 | 0.2571 | 0.9997 | 0.82 | 0.8062 | 0.1471 | 0.0438 |
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+ | No log | 63.0 | 441 | 0.6150 | 0.825 | 0.2560 | 1.0061 | 0.825 | 0.8166 | 0.1498 | 0.0430 |
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+ | No log | 64.0 | 448 | 0.6201 | 0.825 | 0.2574 | 1.0592 | 0.825 | 0.8166 | 0.1369 | 0.0442 |
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+ | No log | 65.0 | 455 | 0.6281 | 0.815 | 0.2601 | 0.9990 | 0.815 | 0.8013 | 0.1449 | 0.0459 |
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+ | No log | 66.0 | 462 | 0.6232 | 0.825 | 0.2538 | 1.0657 | 0.825 | 0.8166 | 0.1341 | 0.0442 |
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+ | No log | 67.0 | 469 | 0.6242 | 0.82 | 0.2567 | 1.0622 | 0.82 | 0.8100 | 0.1432 | 0.0445 |
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+ | No log | 68.0 | 476 | 0.6213 | 0.82 | 0.2598 | 1.0666 | 0.82 | 0.8100 | 0.1517 | 0.0447 |
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+ | No log | 69.0 | 483 | 0.6268 | 0.82 | 0.2577 | 1.0106 | 0.82 | 0.8100 | 0.1365 | 0.0455 |
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+ | No log | 70.0 | 490 | 0.6252 | 0.82 | 0.2579 | 0.9979 | 0.82 | 0.8100 | 0.1395 | 0.0451 |
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+ | No log | 71.0 | 497 | 0.6251 | 0.82 | 0.2589 | 1.0606 | 0.82 | 0.8100 | 0.1485 | 0.0448 |
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+ | 0.3286 | 72.0 | 504 | 0.6212 | 0.825 | 0.2571 | 1.0034 | 0.825 | 0.8166 | 0.1448 | 0.0443 |
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+ | 0.3286 | 73.0 | 511 | 0.6212 | 0.82 | 0.2584 | 0.9940 | 0.82 | 0.8100 | 0.1499 | 0.0444 |
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+ | 0.3286 | 74.0 | 518 | 0.6214 | 0.82 | 0.2576 | 0.9914 | 0.82 | 0.8100 | 0.1411 | 0.0448 |
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+ | 0.3286 | 78.0 | 546 | 0.6220 | 0.82 | 0.2569 | 0.9964 | 0.82 | 0.8100 | 0.1385 | 0.0450 |
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+ | 0.3286 | 82.0 | 574 | 0.6213 | 0.82 | 0.2578 | 0.9958 | 0.82 | 0.8100 | 0.1422 | 0.0449 |
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+ | 0.3286 | 85.0 | 595 | 0.6220 | 0.82 | 0.2579 | 0.9937 | 0.82 | 0.8100 | 0.1628 | 0.0450 |
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+ | 0.3286 | 86.0 | 602 | 0.6207 | 0.82 | 0.2572 | 0.9945 | 0.82 | 0.8100 | 0.1412 | 0.0447 |
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+ | 0.3286 | 87.0 | 609 | 0.6212 | 0.82 | 0.2573 | 0.9940 | 0.82 | 0.8100 | 0.1414 | 0.0447 |
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+ | 0.3286 | 88.0 | 616 | 0.6201 | 0.825 | 0.2570 | 0.9943 | 0.825 | 0.8166 | 0.1366 | 0.0443 |
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+ | 0.3286 | 89.0 | 623 | 0.6210 | 0.82 | 0.2573 | 0.9944 | 0.82 | 0.8100 | 0.1414 | 0.0448 |
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+ | 0.3286 | 90.0 | 630 | 0.6207 | 0.82 | 0.2572 | 0.9942 | 0.82 | 0.8100 | 0.1414 | 0.0447 |
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+ | 0.3286 | 91.0 | 637 | 0.6210 | 0.82 | 0.2572 | 0.9952 | 0.82 | 0.8100 | 0.1415 | 0.0447 |
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+ | 0.3286 | 92.0 | 644 | 0.6205 | 0.82 | 0.2572 | 0.9939 | 0.82 | 0.8100 | 0.1414 | 0.0447 |
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+ | 0.3286 | 94.0 | 658 | 0.6206 | 0.82 | 0.2572 | 0.9945 | 0.82 | 0.8100 | 0.1414 | 0.0447 |
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+ | 0.3286 | 95.0 | 665 | 0.6203 | 0.825 | 0.2568 | 0.9951 | 0.825 | 0.8166 | 0.1370 | 0.0444 |
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+ | 0.3286 | 96.0 | 672 | 0.6205 | 0.82 | 0.2571 | 0.9942 | 0.82 | 0.8100 | 0.1413 | 0.0448 |
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+ | 0.3286 | 97.0 | 679 | 0.6206 | 0.825 | 0.2570 | 0.9943 | 0.825 | 0.8166 | 0.1370 | 0.0445 |
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+ | 0.3286 | 98.0 | 686 | 0.6206 | 0.825 | 0.2570 | 0.9942 | 0.825 | 0.8166 | 0.1370 | 0.0445 |
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+ | 0.3286 | 99.0 | 693 | 0.6206 | 0.825 | 0.2570 | 0.9940 | 0.825 | 0.8166 | 0.1370 | 0.0445 |
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+ | 0.3286 | 100.0 | 700 | 0.6206 | 0.825 | 0.2570 | 0.9939 | 0.825 | 0.8166 | 0.1370 | 0.0444 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.0.dev0
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+ - Pytorch 2.2.0.dev20231112+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
config.json ADDED
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+ {
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+ "_name_or_path": "WinKawaks/vit-tiny-patch16-224",
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+ "architectures": [
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+ "ViTForImageClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "encoder_stride": 16,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 192,
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+ "id2label": {
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+ "0": "ADVE",
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+ "1": "Email",
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+ "2": "Form",
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+ "3": "Letter",
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+ "4": "Memo",
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+ "5": "News",
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+ "6": "Note",
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+ "7": "Report",
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+ "8": "Resume",
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+ "9": "Scientific"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 768,
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+ "label2id": {
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+ "ADVE": 0,
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+ "Email": 1,
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+ "Form": 2,
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+ "Letter": 3,
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+ "Memo": 4,
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+ "News": 5,
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+ "Note": 6,
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+ "Report": 7,
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+ "Resume": 8,
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+ "Scientific": 9
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "vit",
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+ "num_attention_heads": 3,
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+ "num_channels": 3,
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+ "num_hidden_layers": 12,
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+ "patch_size": 16,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.36.0.dev0"
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+ }
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