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# resnet101_rvl-cdip-cnn_rvl_cdip-NK1000_kd_MSE

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: 0.7429
- Accuracy: 0.7853
- Brier Loss: 0.3044
- Nll: 2.0364
- F1 Micro: 0.7853
- F1 Macro: 0.7862
- Ece: 0.0430
- Aurc: 0.0599

## 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   | 9.5443          | 0.0765   | 0.9365     | 3.7373 | 0.0765   | 0.0522   | 0.0360 | 0.9336 |
| 9.4095        | 2.0   | 500   | 7.4542          | 0.0757   | 0.9312     | 2.8468 | 0.0757   | 0.0316   | 0.0425 | 0.8840 |
| 9.4095        | 3.0   | 750   | 5.8933          | 0.0975   | 0.9356     | 3.2058 | 0.0975   | 0.0408   | 0.0798 | 0.8593 |
| 5.9994        | 4.0   | 1000  | 4.3665          | 0.2125   | 0.8700     | 5.3759 | 0.2125   | 0.1290   | 0.0743 | 0.7029 |
| 5.9994        | 5.0   | 1250  | 3.0367          | 0.4415   | 0.6924     | 4.9073 | 0.4415   | 0.4283   | 0.0806 | 0.3570 |
| 3.2184        | 6.0   | 1500  | 2.1589          | 0.579    | 0.5587     | 3.7412 | 0.579    | 0.5771   | 0.0572 | 0.2172 |
| 3.2184        | 7.0   | 1750  | 1.5582          | 0.652    | 0.4673     | 3.0701 | 0.652    | 0.6456   | 0.0517 | 0.1478 |
| 1.6737        | 8.0   | 2000  | 1.3502          | 0.6893   | 0.4266     | 2.8575 | 0.6893   | 0.6860   | 0.0544 | 0.1175 |
| 1.6737        | 9.0   | 2250  | 1.1389          | 0.7188   | 0.3914     | 2.5937 | 0.7188   | 0.7195   | 0.0544 | 0.1006 |
| 1.0789        | 10.0  | 2500  | 1.0563          | 0.7302   | 0.3742     | 2.5043 | 0.7302   | 0.7305   | 0.0618 | 0.0912 |
| 1.0789        | 11.0  | 2750  | 1.0035          | 0.7428   | 0.3604     | 2.4375 | 0.7428   | 0.7441   | 0.0587 | 0.0823 |
| 0.7934        | 12.0  | 3000  | 0.9169          | 0.7548   | 0.3472     | 2.2921 | 0.7548   | 0.7555   | 0.0547 | 0.0762 |
| 0.7934        | 13.0  | 3250  | 0.8628          | 0.7598   | 0.3386     | 2.2849 | 0.7598   | 0.7600   | 0.0550 | 0.0739 |
| 0.6268        | 14.0  | 3500  | 0.8773          | 0.7675   | 0.3362     | 2.2170 | 0.7675   | 0.7692   | 0.0490 | 0.0718 |
| 0.6268        | 15.0  | 3750  | 0.8263          | 0.7682   | 0.3306     | 2.1617 | 0.7682   | 0.7702   | 0.0534 | 0.0704 |
| 0.5269        | 16.0  | 4000  | 0.8422          | 0.7708   | 0.3289     | 2.1907 | 0.7707   | 0.7717   | 0.0524 | 0.0687 |
| 0.5269        | 17.0  | 4250  | 0.8100          | 0.7745   | 0.3241     | 2.1664 | 0.7745   | 0.7761   | 0.0509 | 0.0667 |
| 0.4516        | 18.0  | 4500  | 0.8013          | 0.7778   | 0.3215     | 2.1216 | 0.7778   | 0.7790   | 0.0473 | 0.0669 |
| 0.4516        | 19.0  | 4750  | 0.7911          | 0.7802   | 0.3183     | 2.1224 | 0.7802   | 0.7812   | 0.0476 | 0.0648 |
| 0.4039        | 20.0  | 5000  | 0.7900          | 0.7775   | 0.3197     | 2.0969 | 0.7775   | 0.7797   | 0.0473 | 0.0647 |
| 0.4039        | 21.0  | 5250  | 0.7919          | 0.7792   | 0.3191     | 2.1445 | 0.7792   | 0.7810   | 0.0531 | 0.0652 |
| 0.3563        | 22.0  | 5500  | 0.7960          | 0.7802   | 0.3166     | 2.0849 | 0.7802   | 0.7818   | 0.0478 | 0.0649 |
| 0.3563        | 23.0  | 5750  | 0.7615          | 0.7825   | 0.3128     | 2.0834 | 0.7825   | 0.7833   | 0.0478 | 0.0638 |
| 0.3251        | 24.0  | 6000  | 0.7840          | 0.7792   | 0.3151     | 2.0841 | 0.7792   | 0.7800   | 0.0513 | 0.0648 |
| 0.3251        | 25.0  | 6250  | 0.7837          | 0.7792   | 0.3159     | 2.0889 | 0.7792   | 0.7808   | 0.0485 | 0.0643 |
| 0.2949        | 26.0  | 6500  | 0.7827          | 0.7802   | 0.3158     | 2.0416 | 0.7802   | 0.7819   | 0.0548 | 0.0648 |
| 0.2949        | 27.0  | 6750  | 0.7650          | 0.78     | 0.3130     | 2.0411 | 0.78     | 0.7807   | 0.0506 | 0.0629 |
| 0.2669        | 28.0  | 7000  | 0.7787          | 0.7802   | 0.3133     | 2.0843 | 0.7802   | 0.7810   | 0.0454 | 0.0627 |
| 0.2669        | 29.0  | 7250  | 0.7892          | 0.782    | 0.3163     | 2.0953 | 0.782    | 0.7826   | 0.0508 | 0.0635 |
| 0.2512        | 30.0  | 7500  | 0.7775          | 0.7825   | 0.3126     | 2.0904 | 0.7825   | 0.7837   | 0.0451 | 0.0633 |
| 0.2512        | 31.0  | 7750  | 0.7601          | 0.7817   | 0.3124     | 2.0251 | 0.7817   | 0.7827   | 0.0485 | 0.0627 |
| 0.231         | 32.0  | 8000  | 0.7669          | 0.7833   | 0.3120     | 2.0685 | 0.7833   | 0.7842   | 0.0472 | 0.0629 |
| 0.231         | 33.0  | 8250  | 0.7652          | 0.7847   | 0.3116     | 2.0661 | 0.7847   | 0.7858   | 0.0519 | 0.0625 |
| 0.2172        | 34.0  | 8500  | 0.7637          | 0.7837   | 0.3107     | 2.0264 | 0.7837   | 0.7852   | 0.0487 | 0.0628 |
| 0.2172        | 35.0  | 8750  | 0.7691          | 0.783    | 0.3120     | 2.0535 | 0.7830   | 0.7844   | 0.0438 | 0.0634 |
| 0.2032        | 36.0  | 9000  | 0.7647          | 0.7845   | 0.3093     | 2.0480 | 0.7845   | 0.7852   | 0.0471 | 0.0620 |
| 0.2032        | 37.0  | 9250  | 0.7727          | 0.782    | 0.3122     | 2.0610 | 0.782    | 0.7830   | 0.0493 | 0.0628 |
| 0.1925        | 38.0  | 9500  | 0.7563          | 0.7843   | 0.3085     | 2.0267 | 0.7843   | 0.7849   | 0.0459 | 0.0608 |
| 0.1925        | 39.0  | 9750  | 0.7597          | 0.7835   | 0.3087     | 2.0062 | 0.7835   | 0.7845   | 0.0485 | 0.0614 |
| 0.1823        | 40.0  | 10000 | 0.7611          | 0.7833   | 0.3107     | 2.0007 | 0.7833   | 0.7853   | 0.0479 | 0.0625 |
| 0.1823        | 41.0  | 10250 | 0.7608          | 0.7843   | 0.3076     | 2.0335 | 0.7843   | 0.7854   | 0.0486 | 0.0602 |
| 0.17          | 42.0  | 10500 | 0.7535          | 0.7833   | 0.3096     | 2.0121 | 0.7833   | 0.7844   | 0.0505 | 0.0613 |
| 0.17          | 43.0  | 10750 | 0.7524          | 0.7845   | 0.3066     | 2.0425 | 0.7845   | 0.7856   | 0.0476 | 0.0605 |
| 0.1639        | 44.0  | 11000 | 0.7608          | 0.7808   | 0.3108     | 2.0739 | 0.7808   | 0.7816   | 0.0503 | 0.0618 |
| 0.1639        | 45.0  | 11250 | 0.7560          | 0.786    | 0.3063     | 1.9876 | 0.786    | 0.7868   | 0.0496 | 0.0607 |
| 0.1575        | 46.0  | 11500 | 0.7494          | 0.784    | 0.3063     | 2.0311 | 0.7840   | 0.7846   | 0.0416 | 0.0601 |
| 0.1575        | 47.0  | 11750 | 0.7515          | 0.7857   | 0.3069     | 2.0539 | 0.7857   | 0.7866   | 0.0456 | 0.0609 |
| 0.1493        | 48.0  | 12000 | 0.7511          | 0.7843   | 0.3086     | 2.0325 | 0.7843   | 0.7852   | 0.0552 | 0.0612 |
| 0.1493        | 49.0  | 12250 | 0.7495          | 0.787    | 0.3067     | 2.0231 | 0.787    | 0.7880   | 0.0475 | 0.0605 |
| 0.1425        | 50.0  | 12500 | 0.7538          | 0.7867   | 0.3052     | 2.0267 | 0.7868   | 0.7870   | 0.0507 | 0.0603 |
| 0.1425        | 51.0  | 12750 | 0.7529          | 0.7847   | 0.3081     | 2.0592 | 0.7847   | 0.7859   | 0.0467 | 0.0604 |
| 0.1356        | 52.0  | 13000 | 0.7527          | 0.7808   | 0.3071     | 2.0349 | 0.7808   | 0.7818   | 0.0473 | 0.0607 |
| 0.1356        | 53.0  | 13250 | 0.7451          | 0.7865   | 0.3049     | 2.0368 | 0.7865   | 0.7879   | 0.0484 | 0.0595 |
| 0.1325        | 54.0  | 13500 | 0.7481          | 0.7857   | 0.3056     | 2.0223 | 0.7857   | 0.7869   | 0.0468 | 0.0603 |
| 0.1325        | 55.0  | 13750 | 0.7470          | 0.7835   | 0.3057     | 2.0306 | 0.7835   | 0.7844   | 0.0492 | 0.0601 |
| 0.1264        | 56.0  | 14000 | 0.7471          | 0.7873   | 0.3053     | 2.0336 | 0.7873   | 0.7880   | 0.0519 | 0.0601 |
| 0.1264        | 57.0  | 14250 | 0.7429          | 0.7895   | 0.3032     | 2.0149 | 0.7895   | 0.7903   | 0.0468 | 0.0595 |
| 0.1208        | 58.0  | 14500 | 0.7399          | 0.7885   | 0.3035     | 2.0147 | 0.7885   | 0.7895   | 0.0433 | 0.0596 |
| 0.1208        | 59.0  | 14750 | 0.7518          | 0.786    | 0.3076     | 2.0481 | 0.786    | 0.7873   | 0.0403 | 0.0607 |
| 0.119         | 60.0  | 15000 | 0.7483          | 0.7903   | 0.3058     | 2.0138 | 0.7903   | 0.7914   | 0.0471 | 0.0601 |
| 0.119         | 61.0  | 15250 | 0.7463          | 0.7845   | 0.3043     | 2.0617 | 0.7845   | 0.7855   | 0.0458 | 0.0599 |
| 0.1128        | 62.0  | 15500 | 0.7478          | 0.7875   | 0.3056     | 2.0187 | 0.7875   | 0.7888   | 0.0452 | 0.0604 |
| 0.1128        | 63.0  | 15750 | 0.7510          | 0.784    | 0.3061     | 2.0204 | 0.7840   | 0.7850   | 0.0495 | 0.0605 |
| 0.1109        | 64.0  | 16000 | 0.7424          | 0.786    | 0.3053     | 2.0167 | 0.786    | 0.7871   | 0.0449 | 0.0603 |
| 0.1109        | 65.0  | 16250 | 0.7473          | 0.7885   | 0.3054     | 2.0200 | 0.7885   | 0.7893   | 0.0471 | 0.0600 |
| 0.1078        | 66.0  | 16500 | 0.7467          | 0.7873   | 0.3054     | 2.0224 | 0.7873   | 0.7883   | 0.0482 | 0.0599 |
| 0.1078        | 67.0  | 16750 | 0.7445          | 0.7893   | 0.3039     | 2.0082 | 0.7893   | 0.7895   | 0.0456 | 0.0593 |
| 0.1051        | 68.0  | 17000 | 0.7490          | 0.7873   | 0.3063     | 2.0152 | 0.7873   | 0.7883   | 0.0505 | 0.0602 |
| 0.1051        | 69.0  | 17250 | 0.7490          | 0.785    | 0.3061     | 2.0103 | 0.785    | 0.7861   | 0.0465 | 0.0602 |
| 0.1009        | 70.0  | 17500 | 0.7445          | 0.7875   | 0.3049     | 2.0308 | 0.7875   | 0.7884   | 0.0483 | 0.0598 |
| 0.1009        | 71.0  | 17750 | 0.7490          | 0.7863   | 0.3068     | 2.0260 | 0.7863   | 0.7875   | 0.0495 | 0.0604 |
| 0.0984        | 72.0  | 18000 | 0.7465          | 0.7893   | 0.3059     | 2.0161 | 0.7893   | 0.7906   | 0.0427 | 0.0601 |
| 0.0984        | 73.0  | 18250 | 0.7451          | 0.7873   | 0.3058     | 2.0204 | 0.7873   | 0.7882   | 0.0511 | 0.0605 |
| 0.0966        | 74.0  | 18500 | 0.7445          | 0.7875   | 0.3042     | 2.0227 | 0.7875   | 0.7886   | 0.0495 | 0.0599 |
| 0.0966        | 75.0  | 18750 | 0.7443          | 0.7863   | 0.3040     | 2.0138 | 0.7863   | 0.7872   | 0.0442 | 0.0598 |
| 0.0947        | 76.0  | 19000 | 0.7448          | 0.7865   | 0.3054     | 2.0234 | 0.7865   | 0.7873   | 0.0457 | 0.0598 |
| 0.0947        | 77.0  | 19250 | 0.7448          | 0.7865   | 0.3041     | 2.0110 | 0.7865   | 0.7875   | 0.0508 | 0.0596 |
| 0.0931        | 78.0  | 19500 | 0.7460          | 0.7883   | 0.3040     | 2.0125 | 0.7883   | 0.7895   | 0.0467 | 0.0595 |
| 0.0931        | 79.0  | 19750 | 0.7456          | 0.7883   | 0.3038     | 2.0302 | 0.7883   | 0.7894   | 0.0455 | 0.0596 |
| 0.0899        | 80.0  | 20000 | 0.7469          | 0.788    | 0.3040     | 2.0188 | 0.788    | 0.7892   | 0.0487 | 0.0597 |
| 0.0899        | 81.0  | 20250 | 0.7421          | 0.788    | 0.3041     | 2.0359 | 0.788    | 0.7888   | 0.0427 | 0.0595 |
| 0.0882        | 82.0  | 20500 | 0.7444          | 0.7865   | 0.3051     | 2.0219 | 0.7865   | 0.7875   | 0.0479 | 0.0600 |
| 0.0882        | 83.0  | 20750 | 0.7439          | 0.788    | 0.3039     | 2.0197 | 0.788    | 0.7894   | 0.0439 | 0.0597 |
| 0.0871        | 84.0  | 21000 | 0.7421          | 0.7865   | 0.3040     | 1.9910 | 0.7865   | 0.7876   | 0.0445 | 0.0598 |
| 0.0871        | 85.0  | 21250 | 0.7429          | 0.7887   | 0.3043     | 2.0253 | 0.7887   | 0.7898   | 0.0426 | 0.0597 |
| 0.0869        | 86.0  | 21500 | 0.7442          | 0.7873   | 0.3041     | 2.0156 | 0.7873   | 0.7885   | 0.0488 | 0.0596 |
| 0.0869        | 87.0  | 21750 | 0.7439          | 0.7857   | 0.3051     | 2.0099 | 0.7857   | 0.7867   | 0.0465 | 0.0599 |
| 0.084         | 88.0  | 22000 | 0.7434          | 0.786    | 0.3040     | 1.9926 | 0.786    | 0.7869   | 0.0469 | 0.0598 |
| 0.084         | 89.0  | 22250 | 0.7431          | 0.7873   | 0.3048     | 2.0028 | 0.7873   | 0.7880   | 0.0442 | 0.0599 |
| 0.0821        | 90.0  | 22500 | 0.7447          | 0.7867   | 0.3040     | 2.0349 | 0.7868   | 0.7876   | 0.0477 | 0.0596 |
| 0.0821        | 91.0  | 22750 | 0.7443          | 0.7877   | 0.3051     | 2.0356 | 0.7877   | 0.7887   | 0.0486 | 0.0601 |
| 0.0813        | 92.0  | 23000 | 0.7500          | 0.7873   | 0.3053     | 2.0465 | 0.7873   | 0.7880   | 0.0484 | 0.0601 |
| 0.0813        | 93.0  | 23250 | 0.7449          | 0.788    | 0.3037     | 1.9966 | 0.788    | 0.7890   | 0.0441 | 0.0594 |
| 0.0811        | 94.0  | 23500 | 0.7466          | 0.7897   | 0.3048     | 2.0297 | 0.7897   | 0.7907   | 0.0429 | 0.0600 |
| 0.0811        | 95.0  | 23750 | 0.7482          | 0.7875   | 0.3058     | 2.0319 | 0.7875   | 0.7885   | 0.0464 | 0.0601 |
| 0.0808        | 96.0  | 24000 | 0.7473          | 0.7863   | 0.3055     | 2.0219 | 0.7863   | 0.7874   | 0.0477 | 0.0603 |
| 0.0808        | 97.0  | 24250 | 0.7451          | 0.7855   | 0.3044     | 2.0356 | 0.7855   | 0.7865   | 0.0481 | 0.0594 |
| 0.08          | 98.0  | 24500 | 0.7442          | 0.7857   | 0.3042     | 2.0213 | 0.7857   | 0.7868   | 0.0475 | 0.0595 |
| 0.08          | 99.0  | 24750 | 0.7462          | 0.7863   | 0.3053     | 2.0354 | 0.7863   | 0.7874   | 0.0425 | 0.0599 |
| 0.079         | 100.0 | 25000 | 0.7429          | 0.7853   | 0.3044     | 2.0364 | 0.7853   | 0.7862   | 0.0430 | 0.0599 |


### 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_MSE", "results": []}]}
transformers pytorch resnet image-classification generated_from_trainer base_model:microsoft/resnet-50 license:apache-2.0 autotrain_compatible endpoints_compatible region:us