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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 6_e_200-tiny_tobacco3482_kd_CEKD_t5.0_a0.5
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 6_e_200-tiny_tobacco3482_kd_CEKD_t5.0_a0.5
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.
It achieves the following results on the evaluation set:
- Loss: 0.3932
- Accuracy: 0.83
- Brier Loss: 0.2507
- Nll: 1.3117
- F1 Micro: 0.83
- F1 Macro: 0.8164
- Ece: 0.1915
- Aurc: 0.0602
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Brier Loss | Nll | F1 Micro | F1 Macro | Ece | Aurc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:|
| No log | 1.0 | 25 | 1.5453 | 0.21 | 0.8721 | 5.2626 | 0.2100 | 0.1784 | 0.2602 | 0.7492 |
| No log | 2.0 | 50 | 0.9799 | 0.515 | 0.6132 | 2.7421 | 0.515 | 0.4183 | 0.2927 | 0.2698 |
| No log | 3.0 | 75 | 0.7948 | 0.655 | 0.4888 | 2.6042 | 0.655 | 0.5597 | 0.2331 | 0.1485 |
| No log | 4.0 | 100 | 0.6422 | 0.735 | 0.3906 | 1.6168 | 0.735 | 0.6662 | 0.2448 | 0.1095 |
| No log | 5.0 | 125 | 0.6261 | 0.785 | 0.3475 | 1.1890 | 0.785 | 0.7582 | 0.2616 | 0.0792 |
| No log | 6.0 | 150 | 0.6060 | 0.775 | 0.3402 | 1.3317 | 0.775 | 0.7269 | 0.2750 | 0.0709 |
| No log | 7.0 | 175 | 0.5659 | 0.8 | 0.3459 | 1.4773 | 0.8000 | 0.7741 | 0.2628 | 0.0960 |
| No log | 8.0 | 200 | 0.5339 | 0.81 | 0.3038 | 1.5029 | 0.81 | 0.7882 | 0.2449 | 0.0699 |
| No log | 9.0 | 225 | 0.5429 | 0.805 | 0.3117 | 1.4140 | 0.805 | 0.7840 | 0.2242 | 0.0771 |
| No log | 10.0 | 250 | 0.5337 | 0.815 | 0.3139 | 1.4630 | 0.815 | 0.8167 | 0.2253 | 0.0801 |
| No log | 11.0 | 275 | 0.5257 | 0.815 | 0.3084 | 1.4325 | 0.815 | 0.7943 | 0.2431 | 0.0823 |
| No log | 12.0 | 300 | 0.4704 | 0.81 | 0.2879 | 1.3557 | 0.81 | 0.7859 | 0.2139 | 0.0770 |
| No log | 13.0 | 325 | 0.4828 | 0.81 | 0.2898 | 1.5643 | 0.81 | 0.7767 | 0.2115 | 0.0712 |
| No log | 14.0 | 350 | 0.4579 | 0.815 | 0.2733 | 1.4403 | 0.815 | 0.8061 | 0.1799 | 0.0609 |
| No log | 15.0 | 375 | 0.4642 | 0.815 | 0.2892 | 1.4598 | 0.815 | 0.8017 | 0.1973 | 0.0537 |
| No log | 16.0 | 400 | 0.4378 | 0.84 | 0.2683 | 1.1278 | 0.8400 | 0.8320 | 0.2135 | 0.0545 |
| No log | 17.0 | 425 | 0.4403 | 0.825 | 0.2750 | 1.3817 | 0.825 | 0.8024 | 0.1898 | 0.0511 |
| No log | 18.0 | 450 | 0.4211 | 0.825 | 0.2646 | 1.5604 | 0.825 | 0.8123 | 0.1918 | 0.0538 |
| No log | 19.0 | 475 | 0.4280 | 0.82 | 0.2700 | 1.5824 | 0.82 | 0.8016 | 0.1814 | 0.0587 |
| 0.4177 | 20.0 | 500 | 0.4223 | 0.83 | 0.2649 | 1.8744 | 0.83 | 0.8152 | 0.1885 | 0.0681 |
| 0.4177 | 21.0 | 525 | 0.4219 | 0.835 | 0.2682 | 1.6053 | 0.835 | 0.8252 | 0.1932 | 0.0600 |
| 0.4177 | 22.0 | 550 | 0.3935 | 0.835 | 0.2534 | 1.4134 | 0.835 | 0.8229 | 0.2049 | 0.0680 |
| 0.4177 | 23.0 | 575 | 0.4231 | 0.82 | 0.2651 | 1.7267 | 0.82 | 0.8028 | 0.1943 | 0.0636 |
| 0.4177 | 24.0 | 600 | 0.4135 | 0.845 | 0.2576 | 1.8708 | 0.845 | 0.8304 | 0.1872 | 0.0559 |
| 0.4177 | 25.0 | 625 | 0.4027 | 0.835 | 0.2526 | 1.5970 | 0.835 | 0.8187 | 0.1886 | 0.0645 |
| 0.4177 | 26.0 | 650 | 0.4000 | 0.835 | 0.2513 | 1.7233 | 0.835 | 0.8151 | 0.1998 | 0.0613 |
| 0.4177 | 27.0 | 675 | 0.3956 | 0.83 | 0.2478 | 1.5716 | 0.83 | 0.8143 | 0.1871 | 0.0533 |
| 0.4177 | 28.0 | 700 | 0.3952 | 0.835 | 0.2493 | 1.5638 | 0.835 | 0.8153 | 0.1942 | 0.0593 |
| 0.4177 | 29.0 | 725 | 0.3965 | 0.83 | 0.2509 | 1.5069 | 0.83 | 0.8150 | 0.1811 | 0.0594 |
| 0.4177 | 30.0 | 750 | 0.3935 | 0.835 | 0.2486 | 1.5657 | 0.835 | 0.8168 | 0.1948 | 0.0573 |
| 0.4177 | 31.0 | 775 | 0.3951 | 0.83 | 0.2498 | 1.5061 | 0.83 | 0.8146 | 0.1886 | 0.0591 |
| 0.4177 | 32.0 | 800 | 0.3940 | 0.835 | 0.2506 | 1.5054 | 0.835 | 0.8203 | 0.1991 | 0.0598 |
| 0.4177 | 33.0 | 825 | 0.3935 | 0.84 | 0.2493 | 1.5025 | 0.8400 | 0.8230 | 0.1932 | 0.0590 |
| 0.4177 | 34.0 | 850 | 0.3928 | 0.84 | 0.2485 | 1.5679 | 0.8400 | 0.8227 | 0.1981 | 0.0570 |
| 0.4177 | 35.0 | 875 | 0.3942 | 0.835 | 0.2497 | 1.5670 | 0.835 | 0.8177 | 0.1940 | 0.0592 |
| 0.4177 | 36.0 | 900 | 0.3935 | 0.835 | 0.2491 | 1.5120 | 0.835 | 0.8203 | 0.1931 | 0.0596 |
| 0.4177 | 37.0 | 925 | 0.3932 | 0.835 | 0.2496 | 1.5715 | 0.835 | 0.8203 | 0.1989 | 0.0597 |
| 0.4177 | 38.0 | 950 | 0.3924 | 0.835 | 0.2491 | 1.5091 | 0.835 | 0.8203 | 0.1973 | 0.0606 |
| 0.4177 | 39.0 | 975 | 0.3936 | 0.835 | 0.2500 | 1.5036 | 0.835 | 0.8203 | 0.1954 | 0.0602 |
| 0.0597 | 40.0 | 1000 | 0.3936 | 0.835 | 0.2497 | 1.4602 | 0.835 | 0.8203 | 0.2053 | 0.0597 |
| 0.0597 | 41.0 | 1025 | 0.3936 | 0.835 | 0.2505 | 1.5040 | 0.835 | 0.8203 | 0.2026 | 0.0607 |
| 0.0597 | 42.0 | 1050 | 0.3931 | 0.83 | 0.2500 | 1.4565 | 0.83 | 0.8164 | 0.1961 | 0.0590 |
| 0.0597 | 43.0 | 1075 | 0.3931 | 0.835 | 0.2497 | 1.5208 | 0.835 | 0.8203 | 0.1972 | 0.0591 |
| 0.0597 | 44.0 | 1100 | 0.3932 | 0.835 | 0.2503 | 1.5040 | 0.835 | 0.8203 | 0.2030 | 0.0606 |
| 0.0597 | 45.0 | 1125 | 0.3930 | 0.835 | 0.2502 | 1.4555 | 0.835 | 0.8203 | 0.1992 | 0.0604 |
| 0.0597 | 46.0 | 1150 | 0.3927 | 0.835 | 0.2500 | 1.4553 | 0.835 | 0.8203 | 0.1960 | 0.0616 |
| 0.0597 | 47.0 | 1175 | 0.3928 | 0.835 | 0.2501 | 1.3970 | 0.835 | 0.8203 | 0.1965 | 0.0610 |
| 0.0597 | 48.0 | 1200 | 0.3930 | 0.835 | 0.2498 | 1.3967 | 0.835 | 0.8203 | 0.1989 | 0.0599 |
| 0.0597 | 49.0 | 1225 | 0.3931 | 0.835 | 0.2502 | 1.4578 | 0.835 | 0.8203 | 0.1963 | 0.0606 |
| 0.0597 | 50.0 | 1250 | 0.3932 | 0.835 | 0.2504 | 1.4475 | 0.835 | 0.8203 | 0.1996 | 0.0604 |
| 0.0597 | 51.0 | 1275 | 0.3928 | 0.835 | 0.2500 | 1.3382 | 0.835 | 0.8203 | 0.2002 | 0.0609 |
| 0.0597 | 52.0 | 1300 | 0.3933 | 0.83 | 0.2502 | 1.4424 | 0.83 | 0.8164 | 0.1991 | 0.0597 |
| 0.0597 | 53.0 | 1325 | 0.3933 | 0.83 | 0.2502 | 1.3390 | 0.83 | 0.8164 | 0.1965 | 0.0604 |
| 0.0597 | 54.0 | 1350 | 0.3929 | 0.83 | 0.2502 | 1.3351 | 0.83 | 0.8164 | 0.1914 | 0.0608 |
| 0.0597 | 55.0 | 1375 | 0.3932 | 0.83 | 0.2503 | 1.3422 | 0.83 | 0.8164 | 0.1969 | 0.0608 |
| 0.0597 | 56.0 | 1400 | 0.3934 | 0.83 | 0.2506 | 1.3369 | 0.83 | 0.8164 | 0.1950 | 0.0599 |
| 0.0597 | 57.0 | 1425 | 0.3930 | 0.83 | 0.2502 | 1.3829 | 0.83 | 0.8164 | 0.1966 | 0.0603 |
| 0.0597 | 58.0 | 1450 | 0.3930 | 0.835 | 0.2503 | 1.3219 | 0.835 | 0.8203 | 0.1907 | 0.0607 |
| 0.0597 | 59.0 | 1475 | 0.3930 | 0.83 | 0.2504 | 1.3268 | 0.83 | 0.8164 | 0.1919 | 0.0599 |
| 0.0574 | 60.0 | 1500 | 0.3933 | 0.835 | 0.2505 | 1.3242 | 0.835 | 0.8203 | 0.1913 | 0.0601 |
| 0.0574 | 61.0 | 1525 | 0.3930 | 0.83 | 0.2504 | 1.3205 | 0.83 | 0.8164 | 0.1943 | 0.0607 |
| 0.0574 | 62.0 | 1550 | 0.3930 | 0.83 | 0.2504 | 1.3189 | 0.83 | 0.8164 | 0.1947 | 0.0608 |
| 0.0574 | 63.0 | 1575 | 0.3931 | 0.83 | 0.2504 | 1.3197 | 0.83 | 0.8164 | 0.1917 | 0.0600 |
| 0.0574 | 64.0 | 1600 | 0.3931 | 0.835 | 0.2505 | 1.3200 | 0.835 | 0.8203 | 0.1904 | 0.0597 |
| 0.0574 | 65.0 | 1625 | 0.3932 | 0.83 | 0.2505 | 1.3175 | 0.83 | 0.8164 | 0.1915 | 0.0601 |
| 0.0574 | 66.0 | 1650 | 0.3931 | 0.83 | 0.2506 | 1.3200 | 0.83 | 0.8164 | 0.1917 | 0.0608 |
| 0.0574 | 67.0 | 1675 | 0.3929 | 0.83 | 0.2503 | 1.3188 | 0.83 | 0.8164 | 0.1940 | 0.0598 |
| 0.0574 | 68.0 | 1700 | 0.3931 | 0.83 | 0.2505 | 1.3160 | 0.83 | 0.8164 | 0.1913 | 0.0599 |
| 0.0574 | 69.0 | 1725 | 0.3931 | 0.83 | 0.2505 | 1.3161 | 0.83 | 0.8164 | 0.1941 | 0.0598 |
| 0.0574 | 70.0 | 1750 | 0.3932 | 0.83 | 0.2506 | 1.3171 | 0.83 | 0.8164 | 0.1961 | 0.0608 |
| 0.0574 | 71.0 | 1775 | 0.3930 | 0.83 | 0.2506 | 1.3161 | 0.83 | 0.8164 | 0.1913 | 0.0602 |
| 0.0574 | 72.0 | 1800 | 0.3929 | 0.83 | 0.2505 | 1.3155 | 0.83 | 0.8164 | 0.1960 | 0.0603 |
| 0.0574 | 73.0 | 1825 | 0.3930 | 0.83 | 0.2506 | 1.3152 | 0.83 | 0.8164 | 0.1941 | 0.0601 |
| 0.0574 | 74.0 | 1850 | 0.3930 | 0.83 | 0.2506 | 1.3167 | 0.83 | 0.8164 | 0.1940 | 0.0602 |
| 0.0574 | 75.0 | 1875 | 0.3933 | 0.83 | 0.2507 | 1.3148 | 0.83 | 0.8164 | 0.1918 | 0.0600 |
| 0.0574 | 76.0 | 1900 | 0.3930 | 0.83 | 0.2505 | 1.3146 | 0.83 | 0.8164 | 0.1914 | 0.0602 |
| 0.0574 | 77.0 | 1925 | 0.3930 | 0.83 | 0.2505 | 1.3147 | 0.83 | 0.8164 | 0.1914 | 0.0598 |
| 0.0574 | 78.0 | 1950 | 0.3931 | 0.83 | 0.2506 | 1.3134 | 0.83 | 0.8164 | 0.1942 | 0.0601 |
| 0.0574 | 79.0 | 1975 | 0.3931 | 0.83 | 0.2505 | 1.3137 | 0.83 | 0.8164 | 0.1916 | 0.0598 |
| 0.0573 | 80.0 | 2000 | 0.3931 | 0.83 | 0.2506 | 1.3136 | 0.83 | 0.8164 | 0.1915 | 0.0601 |
| 0.0573 | 81.0 | 2025 | 0.3932 | 0.83 | 0.2506 | 1.3132 | 0.83 | 0.8164 | 0.1915 | 0.0607 |
| 0.0573 | 82.0 | 2050 | 0.3933 | 0.83 | 0.2507 | 1.3142 | 0.83 | 0.8164 | 0.1943 | 0.0603 |
| 0.0573 | 83.0 | 2075 | 0.3933 | 0.83 | 0.2507 | 1.3135 | 0.83 | 0.8164 | 0.1916 | 0.0603 |
| 0.0573 | 84.0 | 2100 | 0.3931 | 0.83 | 0.2506 | 1.3124 | 0.83 | 0.8164 | 0.1914 | 0.0601 |
| 0.0573 | 85.0 | 2125 | 0.3931 | 0.83 | 0.2507 | 1.3128 | 0.83 | 0.8164 | 0.1915 | 0.0602 |
| 0.0573 | 86.0 | 2150 | 0.3931 | 0.83 | 0.2506 | 1.3128 | 0.83 | 0.8164 | 0.1916 | 0.0602 |
| 0.0573 | 87.0 | 2175 | 0.3932 | 0.83 | 0.2507 | 1.3130 | 0.83 | 0.8164 | 0.1943 | 0.0602 |
| 0.0573 | 88.0 | 2200 | 0.3932 | 0.83 | 0.2507 | 1.3123 | 0.83 | 0.8164 | 0.1915 | 0.0602 |
| 0.0573 | 89.0 | 2225 | 0.3932 | 0.83 | 0.2507 | 1.3123 | 0.83 | 0.8164 | 0.1915 | 0.0599 |
| 0.0573 | 90.0 | 2250 | 0.3931 | 0.83 | 0.2507 | 1.3119 | 0.83 | 0.8164 | 0.1915 | 0.0602 |
| 0.0573 | 91.0 | 2275 | 0.3932 | 0.83 | 0.2507 | 1.3121 | 0.83 | 0.8164 | 0.1915 | 0.0602 |
| 0.0573 | 92.0 | 2300 | 0.3932 | 0.83 | 0.2507 | 1.3117 | 0.83 | 0.8164 | 0.1915 | 0.0601 |
| 0.0573 | 93.0 | 2325 | 0.3931 | 0.83 | 0.2507 | 1.3117 | 0.83 | 0.8164 | 0.1915 | 0.0602 |
| 0.0573 | 94.0 | 2350 | 0.3932 | 0.83 | 0.2507 | 1.3120 | 0.83 | 0.8164 | 0.1915 | 0.0602 |
| 0.0573 | 95.0 | 2375 | 0.3932 | 0.83 | 0.2507 | 1.3120 | 0.83 | 0.8164 | 0.1916 | 0.0602 |
| 0.0573 | 96.0 | 2400 | 0.3932 | 0.83 | 0.2507 | 1.3119 | 0.83 | 0.8164 | 0.1915 | 0.0602 |
| 0.0573 | 97.0 | 2425 | 0.3932 | 0.83 | 0.2507 | 1.3118 | 0.83 | 0.8164 | 0.1915 | 0.0601 |
| 0.0573 | 98.0 | 2450 | 0.3932 | 0.83 | 0.2507 | 1.3117 | 0.83 | 0.8164 | 0.1915 | 0.0602 |
| 0.0573 | 99.0 | 2475 | 0.3932 | 0.83 | 0.2507 | 1.3118 | 0.83 | 0.8164 | 0.1915 | 0.0602 |
| 0.0573 | 100.0 | 2500 | 0.3932 | 0.83 | 0.2507 | 1.3117 | 0.83 | 0.8164 | 0.1915 | 0.0602 |
### Framework versions
- Transformers 4.30.2
- Pytorch 1.13.1
- Datasets 2.13.1
- Tokenizers 0.13.3
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