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# resnet101_rvl-cdip-cnn_rvl_cdip-NK1000_kd_CEKD_t2.5_a0.5

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5837
- Accuracy: 0.7867
- Brier Loss: 0.3013
- Nll: 1.9882
- F1 Micro: 0.7868
- F1 Macro: 0.7860
- Ece: 0.0529
- Aurc: 0.0581

## 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: 64
- eval_batch_size: 64
- 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   | 250   | 4.1958          | 0.1035   | 0.9350     | 9.1004 | 0.1035   | 0.0792   | 0.0472 | 0.9013 |
| 4.2322        | 2.0   | 500   | 4.0778          | 0.173    | 0.9251     | 6.5742 | 0.173    | 0.1393   | 0.0993 | 0.7501 |
| 4.2322        | 3.0   | 750   | 3.6484          | 0.339    | 0.8778     | 4.9108 | 0.339    | 0.2957   | 0.2172 | 0.5305 |
| 3.5256        | 4.0   | 1000  | 2.5967          | 0.4592   | 0.6991     | 3.3640 | 0.4592   | 0.4220   | 0.1274 | 0.3285 |
| 3.5256        | 5.0   | 1250  | 2.0345          | 0.5417   | 0.6078     | 3.0118 | 0.5417   | 0.5180   | 0.0976 | 0.2447 |
| 1.9172        | 6.0   | 1500  | 1.4417          | 0.625    | 0.5029     | 2.7890 | 0.625    | 0.6123   | 0.0549 | 0.1623 |
| 1.9172        | 7.0   | 1750  | 1.3298          | 0.639    | 0.4852     | 2.6110 | 0.639    | 0.6320   | 0.0558 | 0.1501 |
| 1.1801        | 8.0   | 2000  | 1.1697          | 0.674    | 0.4473     | 2.4787 | 0.674    | 0.6712   | 0.0466 | 0.1283 |
| 1.1801        | 9.0   | 2250  | 0.9625          | 0.7093   | 0.4020     | 2.3242 | 0.7093   | 0.7085   | 0.0526 | 0.1017 |
| 0.8029        | 10.0  | 2500  | 0.9477          | 0.7215   | 0.3893     | 2.3193 | 0.7215   | 0.7228   | 0.0515 | 0.0971 |
| 0.8029        | 11.0  | 2750  | 0.8527          | 0.7375   | 0.3692     | 2.2785 | 0.7375   | 0.7377   | 0.0490 | 0.0870 |
| 0.5717        | 12.0  | 3000  | 0.7377          | 0.7515   | 0.3470     | 2.1475 | 0.7515   | 0.7529   | 0.0552 | 0.0757 |
| 0.5717        | 13.0  | 3250  | 0.7309          | 0.7498   | 0.3469     | 2.1250 | 0.7498   | 0.7494   | 0.0589 | 0.0758 |
| 0.4414        | 14.0  | 3500  | 0.7165          | 0.7558   | 0.3427     | 2.1045 | 0.7558   | 0.7576   | 0.0582 | 0.0721 |
| 0.4414        | 15.0  | 3750  | 0.6865          | 0.7678   | 0.3319     | 2.0457 | 0.7678   | 0.7688   | 0.0551 | 0.0697 |
| 0.3691        | 16.0  | 4000  | 0.7002          | 0.7662   | 0.3348     | 2.1280 | 0.7663   | 0.7664   | 0.0567 | 0.0698 |
| 0.3691        | 17.0  | 4250  | 0.6896          | 0.7628   | 0.3326     | 2.0750 | 0.7628   | 0.7631   | 0.0608 | 0.0691 |
| 0.3214        | 18.0  | 4500  | 0.6666          | 0.7715   | 0.3258     | 2.0468 | 0.7715   | 0.7707   | 0.0544 | 0.0680 |
| 0.3214        | 19.0  | 4750  | 0.6735          | 0.7702   | 0.3277     | 2.0544 | 0.7702   | 0.7700   | 0.0571 | 0.0681 |
| 0.2914        | 20.0  | 5000  | 0.6607          | 0.772    | 0.3241     | 2.0364 | 0.772    | 0.7729   | 0.0525 | 0.0659 |
| 0.2914        | 21.0  | 5250  | 0.6625          | 0.7688   | 0.3217     | 2.0387 | 0.7688   | 0.7703   | 0.0455 | 0.0664 |
| 0.2653        | 22.0  | 5500  | 0.6543          | 0.775    | 0.3200     | 2.0560 | 0.775    | 0.7752   | 0.0507 | 0.0647 |
| 0.2653        | 23.0  | 5750  | 0.6409          | 0.7725   | 0.3188     | 2.0091 | 0.7725   | 0.7733   | 0.0554 | 0.0647 |
| 0.2482        | 24.0  | 6000  | 0.6452          | 0.7758   | 0.3191     | 2.0256 | 0.7758   | 0.7756   | 0.0502 | 0.0655 |
| 0.2482        | 25.0  | 6250  | 0.6401          | 0.7742   | 0.3196     | 2.0668 | 0.7742   | 0.7745   | 0.0528 | 0.0648 |
| 0.2354        | 26.0  | 6500  | 0.6316          | 0.775    | 0.3171     | 2.0150 | 0.775    | 0.7755   | 0.0555 | 0.0634 |
| 0.2354        | 27.0  | 6750  | 0.6257          | 0.7808   | 0.3147     | 2.0129 | 0.7808   | 0.7808   | 0.0503 | 0.0624 |
| 0.2229        | 28.0  | 7000  | 0.6343          | 0.7778   | 0.3144     | 2.0910 | 0.7778   | 0.7776   | 0.0510 | 0.0624 |
| 0.2229        | 29.0  | 7250  | 0.6206          | 0.781    | 0.3115     | 2.0399 | 0.7810   | 0.7798   | 0.0555 | 0.0606 |
| 0.2147        | 30.0  | 7500  | 0.6262          | 0.777    | 0.3124     | 2.0603 | 0.777    | 0.7772   | 0.0539 | 0.0616 |
| 0.2147        | 31.0  | 7750  | 0.6265          | 0.7788   | 0.3137     | 2.0833 | 0.7788   | 0.7777   | 0.0532 | 0.0614 |
| 0.2058        | 32.0  | 8000  | 0.6134          | 0.7815   | 0.3119     | 2.0369 | 0.7815   | 0.7815   | 0.0514 | 0.0615 |
| 0.2058        | 33.0  | 8250  | 0.6153          | 0.7772   | 0.3133     | 2.0513 | 0.7773   | 0.7772   | 0.0534 | 0.0623 |
| 0.1994        | 34.0  | 8500  | 0.6143          | 0.7853   | 0.3098     | 2.0188 | 0.7853   | 0.7857   | 0.0508 | 0.0611 |
| 0.1994        | 35.0  | 8750  | 0.6096          | 0.7827   | 0.3086     | 2.0134 | 0.7828   | 0.7828   | 0.0512 | 0.0606 |
| 0.1932        | 36.0  | 9000  | 0.6094          | 0.784    | 0.3067     | 2.0151 | 0.7840   | 0.7847   | 0.0471 | 0.0602 |
| 0.1932        | 37.0  | 9250  | 0.6142          | 0.7833   | 0.3111     | 2.0213 | 0.7833   | 0.7829   | 0.0542 | 0.0608 |
| 0.1895        | 38.0  | 9500  | 0.6103          | 0.7812   | 0.3094     | 2.0594 | 0.7812   | 0.7799   | 0.0529 | 0.0603 |
| 0.1895        | 39.0  | 9750  | 0.6059          | 0.781    | 0.3078     | 2.0386 | 0.7810   | 0.7806   | 0.0545 | 0.0607 |
| 0.1848        | 40.0  | 10000 | 0.6042          | 0.782    | 0.3072     | 2.0133 | 0.782    | 0.7824   | 0.0527 | 0.0603 |
| 0.1848        | 41.0  | 10250 | 0.5991          | 0.785    | 0.3043     | 2.0124 | 0.785    | 0.7853   | 0.0496 | 0.0594 |
| 0.1793        | 42.0  | 10500 | 0.6034          | 0.784    | 0.3058     | 2.0607 | 0.7840   | 0.7838   | 0.0490 | 0.0599 |
| 0.1793        | 43.0  | 10750 | 0.6047          | 0.7827   | 0.3068     | 2.0139 | 0.7828   | 0.7819   | 0.0492 | 0.0595 |
| 0.1768        | 44.0  | 11000 | 0.5982          | 0.785    | 0.3057     | 2.0303 | 0.785    | 0.7843   | 0.0473 | 0.0596 |
| 0.1768        | 45.0  | 11250 | 0.6036          | 0.7795   | 0.3087     | 2.0173 | 0.7795   | 0.7788   | 0.0549 | 0.0607 |
| 0.1743        | 46.0  | 11500 | 0.5974          | 0.785    | 0.3060     | 2.0026 | 0.785    | 0.7839   | 0.0478 | 0.0596 |
| 0.1743        | 47.0  | 11750 | 0.5996          | 0.782    | 0.3068     | 2.0144 | 0.782    | 0.7825   | 0.0480 | 0.0598 |
| 0.1707        | 48.0  | 12000 | 0.5958          | 0.7833   | 0.3079     | 2.0344 | 0.7833   | 0.7827   | 0.0500 | 0.0598 |
| 0.1707        | 49.0  | 12250 | 0.5969          | 0.782    | 0.3060     | 2.0162 | 0.782    | 0.7820   | 0.0482 | 0.0597 |
| 0.1683        | 50.0  | 12500 | 0.5933          | 0.784    | 0.3043     | 1.9897 | 0.7840   | 0.7836   | 0.0496 | 0.0589 |
| 0.1683        | 51.0  | 12750 | 0.5935          | 0.7833   | 0.3042     | 2.0142 | 0.7833   | 0.7829   | 0.0501 | 0.0586 |
| 0.1649        | 52.0  | 13000 | 0.5950          | 0.7847   | 0.3050     | 2.0125 | 0.7847   | 0.7851   | 0.0475 | 0.0591 |
| 0.1649        | 53.0  | 13250 | 0.5904          | 0.7837   | 0.3020     | 1.9830 | 0.7837   | 0.7837   | 0.0504 | 0.0584 |
| 0.1636        | 54.0  | 13500 | 0.5926          | 0.785    | 0.3042     | 2.0006 | 0.785    | 0.7845   | 0.0493 | 0.0588 |
| 0.1636        | 55.0  | 13750 | 0.5885          | 0.7847   | 0.3029     | 2.0025 | 0.7847   | 0.7843   | 0.0505 | 0.0585 |
| 0.1616        | 56.0  | 14000 | 0.5920          | 0.788    | 0.3041     | 2.0174 | 0.788    | 0.7878   | 0.0520 | 0.0591 |
| 0.1616        | 57.0  | 14250 | 0.5927          | 0.7863   | 0.3033     | 2.0321 | 0.7863   | 0.7858   | 0.0521 | 0.0588 |
| 0.1592        | 58.0  | 14500 | 0.5878          | 0.787    | 0.3017     | 1.9751 | 0.787    | 0.7874   | 0.0461 | 0.0584 |
| 0.1592        | 59.0  | 14750 | 0.5888          | 0.7867   | 0.3030     | 1.9996 | 0.7868   | 0.7864   | 0.0494 | 0.0582 |
| 0.1585        | 60.0  | 15000 | 0.5929          | 0.786    | 0.3052     | 2.0237 | 0.786    | 0.7857   | 0.0512 | 0.0584 |
| 0.1585        | 61.0  | 15250 | 0.5894          | 0.7865   | 0.3026     | 1.9895 | 0.7865   | 0.7864   | 0.0548 | 0.0585 |
| 0.1562        | 62.0  | 15500 | 0.5903          | 0.7873   | 0.3033     | 1.9670 | 0.7873   | 0.7870   | 0.0481 | 0.0584 |
| 0.1562        | 63.0  | 15750 | 0.5896          | 0.7853   | 0.3023     | 1.9681 | 0.7853   | 0.7850   | 0.0520 | 0.0587 |
| 0.1548        | 64.0  | 16000 | 0.5903          | 0.7847   | 0.3027     | 1.9865 | 0.7847   | 0.7846   | 0.0506 | 0.0587 |
| 0.1548        | 65.0  | 16250 | 0.5910          | 0.7853   | 0.3039     | 2.0009 | 0.7853   | 0.7849   | 0.0515 | 0.0593 |
| 0.1537        | 66.0  | 16500 | 0.5866          | 0.7883   | 0.3012     | 1.9561 | 0.7883   | 0.7881   | 0.0447 | 0.0581 |
| 0.1537        | 67.0  | 16750 | 0.5858          | 0.7867   | 0.3009     | 1.9868 | 0.7868   | 0.7861   | 0.0486 | 0.0577 |
| 0.1526        | 68.0  | 17000 | 0.5886          | 0.7867   | 0.3024     | 2.0009 | 0.7868   | 0.7862   | 0.0530 | 0.0587 |
| 0.1526        | 69.0  | 17250 | 0.5850          | 0.7863   | 0.3010     | 2.0095 | 0.7863   | 0.7860   | 0.0510 | 0.0581 |
| 0.1508        | 70.0  | 17500 | 0.5867          | 0.7865   | 0.3019     | 2.0304 | 0.7865   | 0.7861   | 0.0525 | 0.0583 |
| 0.1508        | 71.0  | 17750 | 0.5895          | 0.7857   | 0.3038     | 2.0013 | 0.7857   | 0.7853   | 0.0478 | 0.0586 |
| 0.15          | 72.0  | 18000 | 0.5894          | 0.7847   | 0.3025     | 2.0051 | 0.7847   | 0.7845   | 0.0500 | 0.0586 |
| 0.15          | 73.0  | 18250 | 0.5867          | 0.7865   | 0.3022     | 1.9634 | 0.7865   | 0.7860   | 0.0489 | 0.0582 |
| 0.149         | 74.0  | 18500 | 0.5888          | 0.7857   | 0.3026     | 1.9817 | 0.7857   | 0.7851   | 0.0497 | 0.0584 |
| 0.149         | 75.0  | 18750 | 0.5823          | 0.7885   | 0.2994     | 1.9873 | 0.7885   | 0.7880   | 0.0476 | 0.0577 |
| 0.1483        | 76.0  | 19000 | 0.5866          | 0.7853   | 0.3025     | 1.9870 | 0.7853   | 0.7849   | 0.0531 | 0.0583 |
| 0.1483        | 77.0  | 19250 | 0.5866          | 0.7867   | 0.3013     | 1.9933 | 0.7868   | 0.7862   | 0.0498 | 0.0577 |
| 0.1478        | 78.0  | 19500 | 0.5844          | 0.787    | 0.3010     | 1.9793 | 0.787    | 0.7868   | 0.0465 | 0.0579 |
| 0.1478        | 79.0  | 19750 | 0.5850          | 0.7857   | 0.3005     | 1.9856 | 0.7857   | 0.7855   | 0.0489 | 0.0580 |
| 0.1463        | 80.0  | 20000 | 0.5829          | 0.7893   | 0.2999     | 2.0003 | 0.7893   | 0.7890   | 0.0543 | 0.0578 |
| 0.1463        | 81.0  | 20250 | 0.5845          | 0.7867   | 0.3011     | 2.0178 | 0.7868   | 0.7864   | 0.0494 | 0.0580 |
| 0.1457        | 82.0  | 20500 | 0.5878          | 0.7865   | 0.3022     | 2.0108 | 0.7865   | 0.7861   | 0.0507 | 0.0583 |
| 0.1457        | 83.0  | 20750 | 0.5862          | 0.7865   | 0.3016     | 1.9996 | 0.7865   | 0.7865   | 0.0505 | 0.0585 |
| 0.1452        | 84.0  | 21000 | 0.5851          | 0.7863   | 0.3011     | 2.0002 | 0.7863   | 0.7859   | 0.0481 | 0.0582 |
| 0.1452        | 85.0  | 21250 | 0.5850          | 0.787    | 0.3013     | 1.9659 | 0.787    | 0.7867   | 0.0524 | 0.0582 |
| 0.1449        | 86.0  | 21500 | 0.5878          | 0.7867   | 0.3023     | 1.9837 | 0.7868   | 0.7866   | 0.0526 | 0.0581 |
| 0.1449        | 87.0  | 21750 | 0.5844          | 0.7873   | 0.3010     | 1.9807 | 0.7873   | 0.7865   | 0.0522 | 0.0577 |
| 0.1437        | 88.0  | 22000 | 0.5846          | 0.7877   | 0.3012     | 1.9947 | 0.7877   | 0.7869   | 0.0464 | 0.0580 |
| 0.1437        | 89.0  | 22250 | 0.5859          | 0.787    | 0.3016     | 2.0002 | 0.787    | 0.7867   | 0.0503 | 0.0581 |
| 0.143         | 90.0  | 22500 | 0.5838          | 0.7865   | 0.3010     | 1.9996 | 0.7865   | 0.7859   | 0.0496 | 0.0576 |
| 0.143         | 91.0  | 22750 | 0.5843          | 0.7837   | 0.3011     | 1.9683 | 0.7837   | 0.7834   | 0.0501 | 0.0583 |
| 0.1426        | 92.0  | 23000 | 0.5843          | 0.7873   | 0.3010     | 1.9960 | 0.7873   | 0.7870   | 0.0524 | 0.0578 |
| 0.1426        | 93.0  | 23250 | 0.5827          | 0.7847   | 0.3005     | 1.9719 | 0.7847   | 0.7844   | 0.0506 | 0.0579 |
| 0.1428        | 94.0  | 23500 | 0.5831          | 0.7865   | 0.3009     | 1.9781 | 0.7865   | 0.7862   | 0.0517 | 0.0579 |
| 0.1428        | 95.0  | 23750 | 0.5821          | 0.784    | 0.3001     | 1.9641 | 0.7840   | 0.7838   | 0.0505 | 0.0579 |
| 0.1424        | 96.0  | 24000 | 0.5850          | 0.7845   | 0.3020     | 1.9667 | 0.7845   | 0.7842   | 0.0526 | 0.0584 |
| 0.1424        | 97.0  | 24250 | 0.5850          | 0.7847   | 0.3012     | 1.9776 | 0.7847   | 0.7844   | 0.0508 | 0.0579 |
| 0.142         | 98.0  | 24500 | 0.5845          | 0.7877   | 0.3011     | 1.9745 | 0.7877   | 0.7870   | 0.0491 | 0.0579 |
| 0.142         | 99.0  | 24750 | 0.5834          | 0.7853   | 0.3010     | 1.9679 | 0.7853   | 0.7852   | 0.0506 | 0.0581 |
| 0.1416        | 100.0 | 25000 | 0.5837          | 0.7867   | 0.3013     | 1.9882 | 0.7868   | 0.7860   | 0.0529 | 0.0581 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.2.0.dev20231002
- Datasets 2.7.1
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/resnet-50", "model-index": [{"name": "resnet101_rvl-cdip-cnn_rvl_cdip-NK1000_kd_CEKD_t2.5_a0.5", "results": []}]}
transformers pytorch resnet image-classification generated_from_trainer base_model:microsoft/resnet-50 license:apache-2.0 autotrain_compatible endpoints_compatible region:us