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# resnet101-base_tobacco-cnn_tobacco3482_hint

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: 24.6607
- Accuracy: 0.57
- Brier Loss: 0.6012
- Nll: 2.9238
- F1 Micro: 0.57
- F1 Macro: 0.5344
- Ece: 0.2496
- Aurc: 0.2274

## 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: 128
- eval_batch_size: 128
- 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   | 7    | 27.2504         | 0.07     | 0.9006     | 8.5876  | 0.07     | 0.0131   | 0.1634 | 0.9646 |
| No log        | 2.0   | 14   | 27.1186         | 0.155    | 0.9229     | 12.2960 | 0.155    | 0.0268   | 0.2967 | 0.8769 |
| No log        | 3.0   | 21   | 27.9163         | 0.155    | 1.3722     | 11.2040 | 0.155    | 0.0268   | 0.6887 | 0.5963 |
| No log        | 4.0   | 28   | 28.2724         | 0.155    | 1.4334     | 9.3615  | 0.155    | 0.0273   | 0.7029 | 0.6185 |
| No log        | 5.0   | 35   | 26.9699         | 0.175    | 1.0316     | 5.3928  | 0.175    | 0.0465   | 0.4168 | 0.5989 |
| No log        | 6.0   | 42   | 26.1797         | 0.23     | 0.8746     | 3.9558  | 0.23     | 0.0993   | 0.3120 | 0.5627 |
| No log        | 7.0   | 49   | 25.8507         | 0.25     | 0.8299     | 3.2357  | 0.25     | 0.1721   | 0.2686 | 0.6618 |
| No log        | 8.0   | 56   | 25.7515         | 0.24     | 0.8336     | 2.7738  | 0.24     | 0.1579   | 0.2670 | 0.6619 |
| No log        | 9.0   | 63   | 25.3041         | 0.39     | 0.7346     | 2.5881  | 0.39     | 0.2914   | 0.2649 | 0.4362 |
| No log        | 10.0  | 70   | 25.1996         | 0.375    | 0.7406     | 2.7338  | 0.375    | 0.2616   | 0.2903 | 0.4923 |
| No log        | 11.0  | 77   | 25.0418         | 0.44     | 0.6756     | 3.2534  | 0.44     | 0.3173   | 0.2520 | 0.3197 |
| No log        | 12.0  | 84   | 25.3664         | 0.35     | 0.8231     | 3.6209  | 0.35     | 0.2628   | 0.2924 | 0.5484 |
| No log        | 13.0  | 91   | 25.0353         | 0.44     | 0.6927     | 3.5523  | 0.44     | 0.3230   | 0.2842 | 0.3332 |
| No log        | 14.0  | 98   | 25.2980         | 0.36     | 0.8265     | 3.3953  | 0.36     | 0.2859   | 0.3158 | 0.5347 |
| No log        | 15.0  | 105  | 24.8521         | 0.425    | 0.6604     | 3.0888  | 0.425    | 0.3379   | 0.2641 | 0.3096 |
| No log        | 16.0  | 112  | 24.8368         | 0.46     | 0.6622     | 2.7863  | 0.46     | 0.3626   | 0.2771 | 0.3429 |
| No log        | 17.0  | 119  | 25.0490         | 0.355    | 0.7909     | 2.9342  | 0.3550   | 0.2764   | 0.3300 | 0.5313 |
| No log        | 18.0  | 126  | 24.9950         | 0.4      | 0.7521     | 3.5010  | 0.4000   | 0.3467   | 0.2801 | 0.4721 |
| No log        | 19.0  | 133  | 24.7232         | 0.505    | 0.6259     | 2.9709  | 0.505    | 0.4017   | 0.2799 | 0.2807 |
| No log        | 20.0  | 140  | 24.7500         | 0.5      | 0.6408     | 3.1274  | 0.5      | 0.4278   | 0.2398 | 0.2752 |
| No log        | 21.0  | 147  | 24.5976         | 0.54     | 0.5922     | 2.7847  | 0.54     | 0.4872   | 0.2422 | 0.2319 |
| No log        | 22.0  | 154  | 24.9329         | 0.42     | 0.7518     | 2.9924  | 0.4200   | 0.3777   | 0.3094 | 0.4446 |
| No log        | 23.0  | 161  | 24.6088         | 0.535    | 0.6089     | 2.8494  | 0.535    | 0.5067   | 0.2756 | 0.2770 |
| No log        | 24.0  | 168  | 25.1851         | 0.39     | 0.8175     | 3.7625  | 0.39     | 0.3513   | 0.3211 | 0.5049 |
| No log        | 25.0  | 175  | 24.5058         | 0.585    | 0.5754     | 2.6524  | 0.585    | 0.5707   | 0.2296 | 0.2227 |
| No log        | 26.0  | 182  | 25.2073         | 0.435    | 0.7812     | 3.0365  | 0.435    | 0.3839   | 0.3190 | 0.5012 |
| No log        | 27.0  | 189  | 24.7752         | 0.54     | 0.6558     | 2.9071  | 0.54     | 0.4667   | 0.2669 | 0.2898 |
| No log        | 28.0  | 196  | 24.8546         | 0.515    | 0.6697     | 2.5989  | 0.515    | 0.4397   | 0.2943 | 0.3817 |
| No log        | 29.0  | 203  | 24.5759         | 0.56     | 0.5969     | 2.6234  | 0.56     | 0.5342   | 0.2609 | 0.2493 |
| No log        | 30.0  | 210  | 24.7052         | 0.53     | 0.6198     | 2.9462  | 0.53     | 0.4811   | 0.2779 | 0.2766 |
| No log        | 31.0  | 217  | 24.5828         | 0.545    | 0.6038     | 2.7967  | 0.545    | 0.4979   | 0.2455 | 0.2369 |
| No log        | 32.0  | 224  | 24.6622         | 0.545    | 0.6220     | 2.8878  | 0.545    | 0.4925   | 0.2854 | 0.2682 |
| No log        | 33.0  | 231  | 24.6253         | 0.57     | 0.5991     | 3.1607  | 0.57     | 0.5327   | 0.2869 | 0.2518 |
| No log        | 34.0  | 238  | 24.6230         | 0.535    | 0.6351     | 2.5626  | 0.535    | 0.5245   | 0.2766 | 0.3077 |
| No log        | 35.0  | 245  | 24.5803         | 0.59     | 0.5900     | 2.8215  | 0.59     | 0.5564   | 0.2724 | 0.2563 |
| No log        | 36.0  | 252  | 24.5679         | 0.57     | 0.5709     | 3.1573  | 0.57     | 0.5089   | 0.2523 | 0.2222 |
| No log        | 37.0  | 259  | 24.5375         | 0.575    | 0.5631     | 2.9349  | 0.575    | 0.5381   | 0.2279 | 0.2007 |
| No log        | 38.0  | 266  | 24.6423         | 0.565    | 0.6072     | 2.6772  | 0.565    | 0.5340   | 0.2587 | 0.2247 |
| No log        | 39.0  | 273  | 24.6706         | 0.575    | 0.6139     | 2.9241  | 0.575    | 0.5291   | 0.2318 | 0.2416 |
| No log        | 40.0  | 280  | 24.6007         | 0.575    | 0.5774     | 2.9918  | 0.575    | 0.5323   | 0.2575 | 0.2138 |
| No log        | 41.0  | 287  | 24.7587         | 0.565    | 0.6231     | 2.9588  | 0.565    | 0.5023   | 0.2685 | 0.2665 |
| No log        | 42.0  | 294  | 24.5681         | 0.56     | 0.5786     | 2.9999  | 0.56     | 0.5153   | 0.2558 | 0.2093 |
| No log        | 43.0  | 301  | 24.5971         | 0.59     | 0.5687     | 3.0595  | 0.59     | 0.5365   | 0.2532 | 0.2004 |
| No log        | 44.0  | 308  | 24.6424         | 0.58     | 0.5918     | 2.9073  | 0.58     | 0.5432   | 0.2470 | 0.2113 |
| No log        | 45.0  | 315  | 24.5998         | 0.58     | 0.5705     | 3.0442  | 0.58     | 0.5488   | 0.2769 | 0.2011 |
| No log        | 46.0  | 322  | 24.5625         | 0.62     | 0.5561     | 2.9855  | 0.62     | 0.5869   | 0.2492 | 0.2069 |
| No log        | 47.0  | 329  | 24.6409         | 0.57     | 0.5817     | 2.8587  | 0.57     | 0.5400   | 0.2480 | 0.2239 |
| No log        | 48.0  | 336  | 24.6218         | 0.57     | 0.5958     | 2.8299  | 0.57     | 0.5426   | 0.2725 | 0.2251 |
| No log        | 49.0  | 343  | 24.5568         | 0.585    | 0.5762     | 2.9178  | 0.585    | 0.5590   | 0.2374 | 0.2102 |
| No log        | 50.0  | 350  | 24.6607         | 0.57     | 0.6012     | 2.9238  | 0.57     | 0.5344   | 0.2496 | 0.2274 |


### 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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