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# resnet101-base_tobacco-cnn_tobacco3482_kd

This model is a fine-tuned version of [bdpc/resnet101-base_tobacco](https://huggingface.co/bdpc/resnet101-base_tobacco) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8158
- Accuracy: 0.565
- Brier Loss: 0.6104
- Nll: 2.6027
- F1 Micro: 0.565
- F1 Macro: 0.4783
- Ece: 0.2677
- Aurc: 0.2516

## 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: 256
- eval_batch_size: 256
- 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Brier Loss | Nll     | F1 Micro | F1 Macro | Ece    | Aurc   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------:|:-------:|:--------:|:--------:|:------:|:------:|
| No log        | 1.0   | 4    | 1.4988          | 0.065    | 0.9007     | 9.6504  | 0.065    | 0.0267   | 0.1512 | 0.9377 |
| No log        | 2.0   | 8    | 1.4615          | 0.155    | 0.8961     | 7.9200  | 0.155    | 0.0268   | 0.2328 | 0.9605 |
| No log        | 3.0   | 12   | 1.4913          | 0.155    | 0.9531     | 11.6402 | 0.155    | 0.0268   | 0.3390 | 0.8899 |
| No log        | 4.0   | 16   | 2.2747          | 0.155    | 1.4111     | 11.0294 | 0.155    | 0.0268   | 0.7077 | 0.7068 |
| No log        | 5.0   | 20   | 2.4543          | 0.155    | 1.4359     | 8.3074  | 0.155    | 0.0268   | 0.7226 | 0.6151 |
| No log        | 6.0   | 24   | 1.9614          | 0.155    | 1.1785     | 6.6431  | 0.155    | 0.0283   | 0.5497 | 0.6022 |
| No log        | 7.0   | 28   | 1.6280          | 0.18     | 0.9978     | 5.8468  | 0.18     | 0.0488   | 0.4014 | 0.6135 |
| No log        | 8.0   | 32   | 1.3465          | 0.225    | 0.8993     | 5.6177  | 0.225    | 0.0740   | 0.3378 | 0.5786 |
| No log        | 9.0   | 36   | 1.2597          | 0.225    | 0.8794     | 5.0542  | 0.225    | 0.0727   | 0.3403 | 0.5658 |
| No log        | 10.0  | 40   | 1.1149          | 0.27     | 0.8181     | 4.5188  | 0.27     | 0.1222   | 0.2890 | 0.5230 |
| No log        | 11.0  | 44   | 0.9805          | 0.31     | 0.7600     | 3.8687  | 0.31     | 0.1726   | 0.2703 | 0.4690 |
| No log        | 12.0  | 48   | 1.0099          | 0.335    | 0.7732     | 3.6652  | 0.335    | 0.2095   | 0.2892 | 0.4739 |
| No log        | 13.0  | 52   | 1.0522          | 0.335    | 0.7919     | 3.3843  | 0.335    | 0.2562   | 0.3006 | 0.6402 |
| No log        | 14.0  | 56   | 1.0566          | 0.32     | 0.7868     | 3.4244  | 0.32     | 0.2373   | 0.3023 | 0.6094 |
| No log        | 15.0  | 60   | 0.9670          | 0.405    | 0.7333     | 3.3926  | 0.405    | 0.3189   | 0.3013 | 0.4037 |
| No log        | 16.0  | 64   | 1.0979          | 0.31     | 0.7877     | 3.3045  | 0.31     | 0.2262   | 0.2792 | 0.5720 |
| No log        | 17.0  | 68   | 0.9022          | 0.44     | 0.6913     | 3.2277  | 0.44     | 0.3429   | 0.2902 | 0.3657 |
| No log        | 18.0  | 72   | 1.2120          | 0.315    | 0.8075     | 4.1289  | 0.315    | 0.2323   | 0.2857 | 0.5909 |
| No log        | 19.0  | 76   | 1.1945          | 0.39     | 0.7974     | 4.2350  | 0.39     | 0.3292   | 0.3271 | 0.5989 |
| No log        | 20.0  | 80   | 1.3861          | 0.345    | 0.7981     | 5.2605  | 0.345    | 0.2700   | 0.2832 | 0.5299 |
| No log        | 21.0  | 84   | 1.2243          | 0.33     | 0.8073     | 4.5262  | 0.33     | 0.2545   | 0.3068 | 0.6133 |
| No log        | 22.0  | 88   | 1.0455          | 0.38     | 0.7238     | 2.7133  | 0.38     | 0.3084   | 0.2901 | 0.4855 |
| No log        | 23.0  | 92   | 0.9044          | 0.45     | 0.6814     | 3.4361  | 0.45     | 0.3273   | 0.2927 | 0.3246 |
| No log        | 24.0  | 96   | 0.8930          | 0.495    | 0.6596     | 3.3412  | 0.495    | 0.4185   | 0.2882 | 0.3070 |
| No log        | 25.0  | 100  | 0.8665          | 0.485    | 0.6534     | 2.9998  | 0.485    | 0.4154   | 0.2641 | 0.3298 |
| No log        | 26.0  | 104  | 1.0458          | 0.375    | 0.7579     | 3.1074  | 0.375    | 0.3333   | 0.2735 | 0.5293 |
| No log        | 27.0  | 108  | 1.0170          | 0.41     | 0.7321     | 2.8884  | 0.41     | 0.3468   | 0.2976 | 0.4566 |
| No log        | 28.0  | 112  | 1.0956          | 0.395    | 0.7464     | 3.3094  | 0.395    | 0.3255   | 0.3154 | 0.4684 |
| No log        | 29.0  | 116  | 1.0805          | 0.39     | 0.7544     | 3.2115  | 0.39     | 0.3193   | 0.3014 | 0.4594 |
| No log        | 30.0  | 120  | 1.2358          | 0.375    | 0.7733     | 4.3992  | 0.375    | 0.3058   | 0.2845 | 0.4876 |
| No log        | 31.0  | 124  | 1.0532          | 0.4      | 0.7458     | 2.7398  | 0.4000   | 0.3614   | 0.2890 | 0.4961 |
| No log        | 32.0  | 128  | 1.0166          | 0.365    | 0.7355     | 2.5093  | 0.3650   | 0.2862   | 0.2728 | 0.5057 |
| No log        | 33.0  | 132  | 0.9395          | 0.48     | 0.6807     | 2.6211  | 0.48     | 0.4394   | 0.2843 | 0.3719 |
| No log        | 34.0  | 136  | 0.8718          | 0.52     | 0.6538     | 2.6802  | 0.52     | 0.4697   | 0.2954 | 0.3051 |
| No log        | 35.0  | 140  | 0.8339          | 0.51     | 0.6362     | 3.1084  | 0.51     | 0.4373   | 0.2654 | 0.3006 |
| No log        | 36.0  | 144  | 0.8411          | 0.51     | 0.6359     | 2.7881  | 0.51     | 0.4286   | 0.2759 | 0.2906 |
| No log        | 37.0  | 148  | 0.8556          | 0.505    | 0.6402     | 2.5519  | 0.505    | 0.4076   | 0.2522 | 0.3060 |
| No log        | 38.0  | 152  | 1.0928          | 0.395    | 0.7438     | 2.8660  | 0.395    | 0.3337   | 0.2815 | 0.4724 |
| No log        | 39.0  | 156  | 1.3830          | 0.39     | 0.8135     | 4.7392  | 0.39     | 0.3094   | 0.2879 | 0.5239 |
| No log        | 40.0  | 160  | 1.2180          | 0.38     | 0.7760     | 3.8384  | 0.38     | 0.3106   | 0.2614 | 0.5109 |
| No log        | 41.0  | 164  | 1.1337          | 0.365    | 0.7486     | 2.8843  | 0.3650   | 0.2948   | 0.2665 | 0.4630 |
| No log        | 42.0  | 168  | 0.8814          | 0.53     | 0.6425     | 2.3353  | 0.53     | 0.4645   | 0.2968 | 0.2973 |
| No log        | 43.0  | 172  | 0.8324          | 0.515    | 0.6174     | 2.4407  | 0.515    | 0.4517   | 0.2847 | 0.2742 |
| No log        | 44.0  | 176  | 0.8477          | 0.53     | 0.6282     | 2.5469  | 0.53     | 0.4615   | 0.2712 | 0.2831 |
| No log        | 45.0  | 180  | 0.8307          | 0.515    | 0.6190     | 2.4871  | 0.515    | 0.4404   | 0.2594 | 0.2845 |
| No log        | 46.0  | 184  | 0.8116          | 0.53     | 0.6070     | 2.4944  | 0.53     | 0.4410   | 0.2337 | 0.2451 |
| No log        | 47.0  | 188  | 0.8349          | 0.54     | 0.6260     | 2.2843  | 0.54     | 0.4423   | 0.2911 | 0.2616 |
| No log        | 48.0  | 192  | 0.8298          | 0.555    | 0.6178     | 2.2946  | 0.555    | 0.4725   | 0.2568 | 0.2482 |
| No log        | 49.0  | 196  | 0.8252          | 0.565    | 0.6141     | 2.3311  | 0.565    | 0.4762   | 0.2810 | 0.2504 |
| No log        | 50.0  | 200  | 0.8158          | 0.565    | 0.6104     | 2.6027  | 0.565    | 0.4783   | 0.2677 | 0.2516 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.2.0.dev20231112+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1

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