Saving best model to hub
Browse files- README.md +166 -0
- config.json +48 -0
- model.safetensors +3 -0
- test-logits.npz +3 -0
- test-references.npz +3 -0
- training_args.bin +3 -0
- validation-logits.npz +3 -0
- 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_og_simkd
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results: []
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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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# dit-base_tobacco-tiny_tobacco3482_og_simkd
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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: 318.4368
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- Accuracy: 0.805
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- Brier Loss: 0.3825
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- Nll: 1.1523
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- F1 Micro: 0.805
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- F1 Macro: 0.7673
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- Ece: 0.2987
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- Aurc: 0.0702
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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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### Training results
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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 | 328.9614 | 0.155 | 0.8984 | 7.4608 | 0.155 | 0.0353 | 0.2035 | 0.8760 |
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| No log | 2.0 | 14 | 328.8199 | 0.235 | 0.8940 | 6.4907 | 0.235 | 0.1148 | 0.2643 | 0.7444 |
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| No log | 3.0 | 21 | 328.4224 | 0.38 | 0.8711 | 2.8184 | 0.38 | 0.3279 | 0.3440 | 0.4817 |
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| No log | 4.0 | 28 | 327.5357 | 0.51 | 0.8072 | 2.0744 | 0.51 | 0.4221 | 0.4111 | 0.3319 |
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| No log | 5.0 | 35 | 326.2037 | 0.53 | 0.6860 | 2.0669 | 0.53 | 0.4313 | 0.3619 | 0.2744 |
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| No log | 6.0 | 42 | 324.8763 | 0.565 | 0.6008 | 1.9437 | 0.565 | 0.4477 | 0.3009 | 0.2469 |
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| No log | 7.0 | 49 | 323.9205 | 0.6 | 0.5390 | 1.7694 | 0.6 | 0.4647 | 0.2365 | 0.1978 |
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| No log | 8.0 | 56 | 323.2227 | 0.65 | 0.4632 | 1.7803 | 0.65 | 0.5195 | 0.2313 | 0.1422 |
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| No log | 9.0 | 63 | 322.5265 | 0.74 | 0.4177 | 1.7538 | 0.74 | 0.6302 | 0.2442 | 0.1113 |
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| No log | 10.0 | 70 | 322.1928 | 0.705 | 0.4013 | 1.5880 | 0.705 | 0.5864 | 0.2147 | 0.1118 |
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| No log | 11.0 | 77 | 322.2687 | 0.795 | 0.4006 | 1.2854 | 0.795 | 0.7476 | 0.2719 | 0.0942 |
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| No log | 12.0 | 84 | 321.6652 | 0.725 | 0.3754 | 1.3462 | 0.7250 | 0.6521 | 0.2238 | 0.0920 |
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| No log | 13.0 | 91 | 322.3688 | 0.785 | 0.3951 | 1.3209 | 0.785 | 0.7260 | 0.2712 | 0.0805 |
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| No log | 14.0 | 98 | 321.7083 | 0.72 | 0.3915 | 1.4854 | 0.72 | 0.6220 | 0.1963 | 0.0986 |
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| No log | 15.0 | 105 | 321.6171 | 0.8 | 0.3614 | 1.3397 | 0.8000 | 0.7427 | 0.2531 | 0.0741 |
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| No log | 16.0 | 112 | 321.0427 | 0.77 | 0.3502 | 1.1461 | 0.7700 | 0.7082 | 0.1976 | 0.0769 |
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| No log | 17.0 | 119 | 321.1529 | 0.735 | 0.3827 | 1.5751 | 0.735 | 0.6769 | 0.1926 | 0.0973 |
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| No log | 18.0 | 126 | 321.0808 | 0.78 | 0.3611 | 1.2529 | 0.78 | 0.7199 | 0.2242 | 0.0762 |
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| No log | 19.0 | 133 | 321.6684 | 0.795 | 0.3835 | 1.1789 | 0.795 | 0.7506 | 0.2823 | 0.0712 |
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| No log | 20.0 | 140 | 321.2322 | 0.78 | 0.3682 | 1.1715 | 0.78 | 0.7356 | 0.2532 | 0.0752 |
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| No log | 21.0 | 147 | 320.4927 | 0.795 | 0.3458 | 1.3764 | 0.795 | 0.7504 | 0.2178 | 0.0710 |
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| No log | 22.0 | 154 | 320.8896 | 0.8 | 0.3568 | 1.0908 | 0.8000 | 0.7536 | 0.2709 | 0.0677 |
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| No log | 23.0 | 161 | 320.9060 | 0.785 | 0.3774 | 1.1571 | 0.785 | 0.7414 | 0.2712 | 0.0719 |
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| No log | 24.0 | 168 | 320.9026 | 0.795 | 0.3718 | 1.0871 | 0.795 | 0.7465 | 0.2718 | 0.0690 |
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| No log | 25.0 | 175 | 320.7932 | 0.805 | 0.3601 | 1.0998 | 0.805 | 0.7699 | 0.2620 | 0.0614 |
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| No log | 26.0 | 182 | 321.2285 | 0.735 | 0.4164 | 1.8530 | 0.735 | 0.7051 | 0.2814 | 0.0889 |
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| No log | 27.0 | 189 | 320.8364 | 0.775 | 0.4028 | 1.4063 | 0.775 | 0.7412 | 0.2687 | 0.0836 |
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| No log | 28.0 | 196 | 320.0800 | 0.785 | 0.3548 | 1.2123 | 0.785 | 0.7394 | 0.2055 | 0.0740 |
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| No log | 29.0 | 203 | 319.9995 | 0.79 | 0.3526 | 1.2296 | 0.79 | 0.7381 | 0.2363 | 0.0691 |
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| No log | 30.0 | 210 | 320.0685 | 0.795 | 0.3588 | 1.2765 | 0.795 | 0.7447 | 0.2310 | 0.0725 |
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| No log | 31.0 | 217 | 320.0981 | 0.805 | 0.3699 | 1.0128 | 0.805 | 0.7690 | 0.2868 | 0.0701 |
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| No log | 32.0 | 224 | 320.5063 | 0.8 | 0.3900 | 1.1437 | 0.8000 | 0.7650 | 0.3141 | 0.0679 |
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| No log | 33.0 | 231 | 319.8609 | 0.795 | 0.3549 | 1.2051 | 0.795 | 0.7526 | 0.2485 | 0.0697 |
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| No log | 34.0 | 238 | 319.6974 | 0.81 | 0.3600 | 1.0124 | 0.81 | 0.7724 | 0.2671 | 0.0672 |
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| No log | 35.0 | 245 | 319.5988 | 0.795 | 0.3513 | 1.1480 | 0.795 | 0.7540 | 0.2425 | 0.0679 |
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| No log | 36.0 | 252 | 319.6317 | 0.8 | 0.3544 | 1.2190 | 0.8000 | 0.7607 | 0.2449 | 0.0674 |
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| No log | 37.0 | 259 | 319.6821 | 0.81 | 0.3531 | 1.0714 | 0.81 | 0.7672 | 0.2590 | 0.0662 |
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| No log | 38.0 | 266 | 319.7618 | 0.805 | 0.3754 | 1.0421 | 0.805 | 0.7625 | 0.2973 | 0.0701 |
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| No log | 39.0 | 273 | 319.9920 | 0.775 | 0.3843 | 1.0821 | 0.775 | 0.7374 | 0.2801 | 0.0723 |
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| No log | 40.0 | 280 | 319.3407 | 0.765 | 0.3633 | 1.2213 | 0.765 | 0.7041 | 0.2274 | 0.0767 |
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| No log | 41.0 | 287 | 319.2732 | 0.765 | 0.3696 | 1.2638 | 0.765 | 0.7184 | 0.2315 | 0.0835 |
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| No log | 42.0 | 294 | 319.5948 | 0.805 | 0.3685 | 1.0782 | 0.805 | 0.7625 | 0.2678 | 0.0661 |
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| No log | 43.0 | 301 | 319.7181 | 0.8 | 0.3776 | 1.0004 | 0.8000 | 0.7507 | 0.2598 | 0.0672 |
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| No log | 44.0 | 308 | 319.1170 | 0.77 | 0.3619 | 1.2129 | 0.7700 | 0.7159 | 0.2557 | 0.0787 |
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| No log | 45.0 | 315 | 319.5949 | 0.8 | 0.3809 | 1.1448 | 0.8000 | 0.7670 | 0.2868 | 0.0688 |
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| No log | 46.0 | 322 | 319.0327 | 0.79 | 0.3675 | 1.2386 | 0.79 | 0.7315 | 0.2546 | 0.0790 |
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| No log | 47.0 | 329 | 319.3806 | 0.805 | 0.3665 | 1.1368 | 0.805 | 0.7620 | 0.2737 | 0.0700 |
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| No log | 48.0 | 336 | 319.4999 | 0.795 | 0.3836 | 1.0256 | 0.795 | 0.7550 | 0.2800 | 0.0748 |
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| No log | 49.0 | 343 | 319.2553 | 0.8 | 0.3660 | 1.2011 | 0.8000 | 0.7573 | 0.2698 | 0.0679 |
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| No log | 50.0 | 350 | 319.3495 | 0.805 | 0.3836 | 1.1055 | 0.805 | 0.7634 | 0.3004 | 0.0671 |
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| No log | 51.0 | 357 | 319.1643 | 0.8 | 0.3660 | 1.1980 | 0.8000 | 0.7497 | 0.2641 | 0.0709 |
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| No log | 52.0 | 364 | 319.1483 | 0.795 | 0.3651 | 1.0776 | 0.795 | 0.7561 | 0.2856 | 0.0683 |
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| No log | 53.0 | 371 | 319.0104 | 0.79 | 0.3724 | 1.1653 | 0.79 | 0.7422 | 0.2512 | 0.0724 |
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| No log | 54.0 | 378 | 319.1622 | 0.795 | 0.3814 | 1.2807 | 0.795 | 0.7456 | 0.2644 | 0.0759 |
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| No log | 55.0 | 385 | 319.1554 | 0.8 | 0.3694 | 1.2710 | 0.8000 | 0.7570 | 0.2877 | 0.0667 |
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| No log | 56.0 | 392 | 319.2158 | 0.79 | 0.3795 | 1.1678 | 0.79 | 0.7509 | 0.2942 | 0.0692 |
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| No log | 57.0 | 399 | 319.1813 | 0.795 | 0.3839 | 1.1243 | 0.795 | 0.7529 | 0.2835 | 0.0733 |
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| No log | 58.0 | 406 | 318.7599 | 0.81 | 0.3632 | 1.1484 | 0.81 | 0.7738 | 0.3030 | 0.0691 |
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| No log | 59.0 | 413 | 319.0827 | 0.805 | 0.3792 | 1.2070 | 0.805 | 0.7685 | 0.2901 | 0.0674 |
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| No log | 60.0 | 420 | 318.6928 | 0.805 | 0.3661 | 1.1517 | 0.805 | 0.7534 | 0.2492 | 0.0719 |
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| No log | 61.0 | 427 | 318.8309 | 0.805 | 0.3714 | 1.2785 | 0.805 | 0.7517 | 0.2674 | 0.0699 |
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| No log | 62.0 | 434 | 318.9468 | 0.8 | 0.3794 | 1.1549 | 0.8000 | 0.7566 | 0.2862 | 0.0707 |
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| No log | 63.0 | 441 | 318.8059 | 0.785 | 0.3774 | 1.2460 | 0.785 | 0.7487 | 0.2721 | 0.0752 |
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| No log | 64.0 | 448 | 318.7155 | 0.81 | 0.3659 | 1.1963 | 0.81 | 0.7660 | 0.2676 | 0.0680 |
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| No log | 65.0 | 455 | 318.8439 | 0.795 | 0.3799 | 1.0230 | 0.795 | 0.7464 | 0.2797 | 0.0700 |
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| No log | 66.0 | 462 | 318.7784 | 0.79 | 0.3783 | 1.3168 | 0.79 | 0.7503 | 0.2618 | 0.0804 |
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| No log | 67.0 | 469 | 318.9019 | 0.795 | 0.3802 | 1.2003 | 0.795 | 0.7503 | 0.2934 | 0.0702 |
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| No log | 68.0 | 476 | 318.6647 | 0.8 | 0.3728 | 1.1395 | 0.8000 | 0.7590 | 0.2718 | 0.0699 |
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| No log | 69.0 | 483 | 318.3780 | 0.8 | 0.3688 | 1.2812 | 0.8000 | 0.7602 | 0.2690 | 0.0728 |
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| No log | 70.0 | 490 | 318.8004 | 0.8 | 0.3779 | 1.0682 | 0.8000 | 0.7607 | 0.2887 | 0.0682 |
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| No log | 71.0 | 497 | 318.7021 | 0.8 | 0.3748 | 1.1101 | 0.8000 | 0.7545 | 0.2977 | 0.0691 |
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| 322.4844 | 72.0 | 504 | 318.3595 | 0.79 | 0.3779 | 1.2333 | 0.79 | 0.7386 | 0.2617 | 0.0843 |
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| 322.4844 | 73.0 | 511 | 318.5725 | 0.805 | 0.3740 | 1.2108 | 0.805 | 0.7674 | 0.2762 | 0.0677 |
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| 322.4844 | 74.0 | 518 | 318.7131 | 0.81 | 0.3822 | 1.2048 | 0.81 | 0.7660 | 0.2971 | 0.0696 |
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| 322.4844 | 75.0 | 525 | 318.6258 | 0.775 | 0.3806 | 1.1511 | 0.775 | 0.7228 | 0.2824 | 0.0743 |
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| 322.4844 | 76.0 | 532 | 318.5414 | 0.8 | 0.3746 | 1.2136 | 0.8000 | 0.7563 | 0.2872 | 0.0708 |
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| 322.4844 | 77.0 | 539 | 318.5404 | 0.795 | 0.3765 | 1.1414 | 0.795 | 0.7551 | 0.2905 | 0.0707 |
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| 322.4844 | 78.0 | 546 | 318.5820 | 0.8 | 0.3806 | 1.1653 | 0.8000 | 0.7573 | 0.2888 | 0.0707 |
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| 322.4844 | 79.0 | 553 | 318.5909 | 0.8 | 0.3838 | 1.2343 | 0.8000 | 0.7563 | 0.2778 | 0.0754 |
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| 322.4844 | 80.0 | 560 | 318.6398 | 0.795 | 0.3874 | 1.1097 | 0.795 | 0.7520 | 0.3045 | 0.0727 |
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| 322.4844 | 81.0 | 567 | 318.6250 | 0.795 | 0.3860 | 1.1612 | 0.795 | 0.7542 | 0.3079 | 0.0727 |
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| 322.4844 | 82.0 | 574 | 318.5269 | 0.795 | 0.3825 | 1.2812 | 0.795 | 0.7451 | 0.2723 | 0.0737 |
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| 322.4844 | 83.0 | 581 | 318.5790 | 0.795 | 0.3846 | 1.1575 | 0.795 | 0.7455 | 0.2984 | 0.0723 |
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| 322.4844 | 84.0 | 588 | 318.4343 | 0.795 | 0.3826 | 1.2088 | 0.795 | 0.7532 | 0.2852 | 0.0746 |
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| 322.4844 | 85.0 | 595 | 318.3853 | 0.795 | 0.3792 | 1.2784 | 0.795 | 0.7456 | 0.3003 | 0.0729 |
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| 322.4844 | 86.0 | 602 | 318.5143 | 0.805 | 0.3854 | 1.1745 | 0.805 | 0.7636 | 0.3071 | 0.0705 |
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| 322.4844 | 87.0 | 609 | 318.3533 | 0.805 | 0.3763 | 1.1579 | 0.805 | 0.7679 | 0.2805 | 0.0694 |
|
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| 322.4844 | 88.0 | 616 | 318.4745 | 0.795 | 0.3860 | 1.0964 | 0.795 | 0.7539 | 0.2952 | 0.0712 |
|
147 |
+
| 322.4844 | 89.0 | 623 | 318.4909 | 0.805 | 0.3829 | 1.1544 | 0.805 | 0.7673 | 0.3035 | 0.0700 |
|
148 |
+
| 322.4844 | 90.0 | 630 | 318.4910 | 0.8 | 0.3828 | 1.1537 | 0.8000 | 0.7497 | 0.2730 | 0.0717 |
|
149 |
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| 322.4844 | 91.0 | 637 | 318.5176 | 0.8 | 0.3855 | 1.1613 | 0.8000 | 0.7552 | 0.2815 | 0.0718 |
|
150 |
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| 322.4844 | 92.0 | 644 | 318.4100 | 0.795 | 0.3810 | 1.2215 | 0.795 | 0.7532 | 0.2696 | 0.0731 |
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| 322.4844 | 93.0 | 651 | 318.3500 | 0.805 | 0.3765 | 1.2181 | 0.805 | 0.7702 | 0.2790 | 0.0705 |
|
152 |
+
| 322.4844 | 94.0 | 658 | 318.3257 | 0.805 | 0.3785 | 1.2218 | 0.805 | 0.7678 | 0.3114 | 0.0704 |
|
153 |
+
| 322.4844 | 95.0 | 665 | 318.3990 | 0.8 | 0.3823 | 1.1485 | 0.8000 | 0.7585 | 0.2901 | 0.0710 |
|
154 |
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| 322.4844 | 96.0 | 672 | 318.5006 | 0.81 | 0.3862 | 1.1518 | 0.81 | 0.7724 | 0.2925 | 0.0698 |
|
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+
| 322.4844 | 97.0 | 679 | 318.3142 | 0.8 | 0.3780 | 1.1608 | 0.8000 | 0.7557 | 0.2916 | 0.0716 |
|
156 |
+
| 322.4844 | 98.0 | 686 | 318.3767 | 0.795 | 0.3819 | 1.2208 | 0.795 | 0.7526 | 0.2764 | 0.0731 |
|
157 |
+
| 322.4844 | 99.0 | 693 | 318.4233 | 0.8 | 0.3810 | 1.1532 | 0.8000 | 0.7557 | 0.2786 | 0.0706 |
|
158 |
+
| 322.4844 | 100.0 | 700 | 318.4368 | 0.805 | 0.3825 | 1.1523 | 0.805 | 0.7673 | 0.2987 | 0.0702 |
|
159 |
+
|
160 |
+
|
161 |
+
### Framework versions
|
162 |
+
|
163 |
+
- Transformers 4.36.0.dev0
|
164 |
+
- Pytorch 2.2.0.dev20231112+cu118
|
165 |
+
- Datasets 2.14.5
|
166 |
+
- Tokenizers 0.14.1
|
config.json
ADDED
@@ -0,0 +1,48 @@
|
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|
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|
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|
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|
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|
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|
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|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "WinKawaks/vit-tiny-patch16-224",
|
3 |
+
"architectures": [
|
4 |
+
"ViTForImageClassification"
|
5 |
+
],
|
6 |
+
"attention_probs_dropout_prob": 0.0,
|
7 |
+
"encoder_stride": 16,
|
8 |
+
"hidden_act": "gelu",
|
9 |
+
"hidden_dropout_prob": 0.0,
|
10 |
+
"hidden_size": 192,
|
11 |
+
"id2label": {
|
12 |
+
"0": "ADVE",
|
13 |
+
"1": "Email",
|
14 |
+
"2": "Form",
|
15 |
+
"3": "Letter",
|
16 |
+
"4": "Memo",
|
17 |
+
"5": "News",
|
18 |
+
"6": "Note",
|
19 |
+
"7": "Report",
|
20 |
+
"8": "Resume",
|
21 |
+
"9": "Scientific"
|
22 |
+
},
|
23 |
+
"image_size": 224,
|
24 |
+
"initializer_range": 0.02,
|
25 |
+
"intermediate_size": 768,
|
26 |
+
"label2id": {
|
27 |
+
"ADVE": 0,
|
28 |
+
"Email": 1,
|
29 |
+
"Form": 2,
|
30 |
+
"Letter": 3,
|
31 |
+
"Memo": 4,
|
32 |
+
"News": 5,
|
33 |
+
"Note": 6,
|
34 |
+
"Report": 7,
|
35 |
+
"Resume": 8,
|
36 |
+
"Scientific": 9
|
37 |
+
},
|
38 |
+
"layer_norm_eps": 1e-12,
|
39 |
+
"model_type": "vit",
|
40 |
+
"num_attention_heads": 3,
|
41 |
+
"num_channels": 3,
|
42 |
+
"num_hidden_layers": 12,
|
43 |
+
"patch_size": 16,
|
44 |
+
"problem_type": "single_label_classification",
|
45 |
+
"qkv_bias": true,
|
46 |
+
"torch_dtype": "float32",
|
47 |
+
"transformers_version": "4.36.0.dev0"
|
48 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d59d8769e24a1e2b6b1117bc4dc6f7705094828fd21a868c9180d7b9870647e4
|
3 |
+
size 28937528
|
test-logits.npz
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8a645310da8778df9238016367f31c3dacbd53b3b1a662faa90dd1522a348df1
|
3 |
+
size 92099
|
test-references.npz
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:a2afcfdc977d6e963da44f7d0b6169569f722c36f36eb2c2798b49630510363b
|
3 |
+
size 2128
|
training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:334f069b11159752a11ec8ab3e6814529497528296ea36b78447376ec3af28d0
|
3 |
+
size 4856
|
validation-logits.npz
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:82cb288fe432f6ea3ccc8eedde0dd9a6abbbe47ec252f2beb59db756fafb2971
|
3 |
+
size 7636
|
validation-references.npz
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:0354b78de1e153edfd908a412b596b1a05abea3df9a94323763cbb1ee2631790
|
3 |
+
size 423
|