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# dit-small_tobacco3482_kd_MSE

This model is a fine-tuned version of [microsoft/dit-base](https://huggingface.co/microsoft/dit-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 6.7275
- Accuracy: 0.21
- Brier Loss: 0.8834
- Nll: 6.7677
- F1 Micro: 0.2100
- F1 Macro: 0.1146
- Ece: 0.2647
- Aurc: 0.7666

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Brier Loss | Nll     | F1 Micro | F1 Macro | Ece    | Aurc   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------:|:-------:|:--------:|:--------:|:------:|:------:|
| No log        | 0.96  | 3    | 7.1014          | 0.06     | 0.9055     | 7.9056  | 0.06     | 0.0114   | 0.1732 | 0.9050 |
| No log        | 1.96  | 6    | 6.9659          | 0.125    | 0.8970     | 10.1253 | 0.125    | 0.0631   | 0.2010 | 0.8465 |
| No log        | 2.96  | 9    | 6.8528          | 0.075    | 0.8954     | 7.0315  | 0.075    | 0.0258   | 0.1912 | 0.8871 |
| No log        | 3.96  | 12   | 6.8522          | 0.205    | 0.8955     | 7.0990  | 0.205    | 0.0776   | 0.2426 | 0.7588 |
| No log        | 4.96  | 15   | 6.8465          | 0.19     | 0.8959     | 7.1340  | 0.19     | 0.0627   | 0.2308 | 0.7536 |
| No log        | 5.96  | 18   | 6.8246          | 0.205    | 0.8937     | 7.1101  | 0.205    | 0.0867   | 0.2410 | 0.7354 |
| No log        | 6.96  | 21   | 6.8054          | 0.085    | 0.8918     | 7.0215  | 0.085    | 0.0435   | 0.1847 | 0.8289 |
| No log        | 7.96  | 24   | 6.8025          | 0.22     | 0.8879     | 6.8272  | 0.22     | 0.0967   | 0.2487 | 0.7438 |
| No log        | 8.96  | 27   | 6.8045          | 0.21     | 0.8871     | 6.3740  | 0.2100   | 0.0992   | 0.2412 | 0.7634 |
| No log        | 9.96  | 30   | 6.8013          | 0.22     | 0.8869     | 6.9538  | 0.22     | 0.1016   | 0.2495 | 0.7633 |
| No log        | 10.96 | 33   | 6.7920          | 0.215    | 0.8865     | 6.9670  | 0.2150   | 0.0968   | 0.2549 | 0.7577 |
| No log        | 11.96 | 36   | 6.7817          | 0.22     | 0.8867     | 6.9953  | 0.22     | 0.1004   | 0.2455 | 0.7437 |
| No log        | 12.96 | 39   | 6.7729          | 0.17     | 0.8884     | 6.9738  | 0.17     | 0.0891   | 0.2277 | 0.7865 |
| No log        | 13.96 | 42   | 6.7632          | 0.2      | 0.8873     | 6.9622  | 0.2000   | 0.0998   | 0.2393 | 0.7413 |
| No log        | 14.96 | 45   | 6.7548          | 0.215    | 0.8860     | 6.9576  | 0.2150   | 0.1010   | 0.2635 | 0.7189 |
| No log        | 15.96 | 48   | 6.7489          | 0.22     | 0.8857     | 6.8386  | 0.22     | 0.1024   | 0.2665 | 0.7098 |
| No log        | 16.96 | 51   | 6.7457          | 0.23     | 0.8855     | 6.8730  | 0.23     | 0.1129   | 0.2506 | 0.7217 |
| No log        | 17.96 | 54   | 6.7455          | 0.215    | 0.8864     | 6.8688  | 0.2150   | 0.1058   | 0.2576 | 0.7528 |
| No log        | 18.96 | 57   | 6.7424          | 0.16     | 0.8861     | 6.8631  | 0.16     | 0.0843   | 0.2281 | 0.8036 |
| No log        | 19.96 | 60   | 6.7380          | 0.155    | 0.8850     | 6.8443  | 0.155    | 0.0871   | 0.2315 | 0.7937 |
| No log        | 20.96 | 63   | 6.7348          | 0.195    | 0.8841     | 6.7769  | 0.195    | 0.0949   | 0.2501 | 0.7799 |
| No log        | 21.96 | 66   | 6.7317          | 0.175    | 0.8838     | 6.7692  | 0.175    | 0.1025   | 0.2421 | 0.7797 |
| No log        | 22.96 | 69   | 6.7293          | 0.175    | 0.8836     | 6.7682  | 0.175    | 0.1012   | 0.2452 | 0.7799 |
| No log        | 23.96 | 72   | 6.7281          | 0.205    | 0.8834     | 6.7672  | 0.205    | 0.1132   | 0.2566 | 0.7679 |
| No log        | 24.96 | 75   | 6.7275          | 0.21     | 0.8834     | 6.7677  | 0.2100   | 0.1146   | 0.2647 | 0.7666 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2

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