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# dit-small_tobacco3482_kd_CEKD_t2.5_a0.5

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: 3.8936
- Accuracy: 0.185
- Brier Loss: 0.8707
- Nll: 6.6284
- F1 Micro: 0.185
- F1 Macro: 0.0488
- Ece: 0.2527
- Aurc: 0.7434

## 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    | 4.2363          | 0.06     | 0.9043     | 9.2962 | 0.06     | 0.0114   | 0.1758 | 0.9032 |
| No log        | 1.96  | 6    | 4.1268          | 0.18     | 0.8887     | 6.8683 | 0.18     | 0.0305   | 0.2329 | 0.8055 |
| No log        | 2.96  | 9    | 4.0044          | 0.18     | 0.8773     | 7.3055 | 0.18     | 0.0305   | 0.2510 | 0.8219 |
| No log        | 3.96  | 12   | 3.9678          | 0.18     | 0.8851     | 7.2435 | 0.18     | 0.0305   | 0.2677 | 0.8214 |
| No log        | 4.96  | 15   | 3.9645          | 0.185    | 0.8877     | 6.9806 | 0.185    | 0.0488   | 0.2757 | 0.7934 |
| No log        | 5.96  | 18   | 3.9635          | 0.185    | 0.8853     | 6.9543 | 0.185    | 0.0488   | 0.2551 | 0.7812 |
| No log        | 6.96  | 21   | 3.9564          | 0.185    | 0.8801     | 6.0556 | 0.185    | 0.0488   | 0.2515 | 0.7771 |
| No log        | 7.96  | 24   | 3.9505          | 0.185    | 0.8772     | 6.0356 | 0.185    | 0.0488   | 0.2598 | 0.7724 |
| No log        | 8.96  | 27   | 3.9435          | 0.185    | 0.8751     | 6.0288 | 0.185    | 0.0488   | 0.2590 | 0.7697 |
| No log        | 9.96  | 30   | 3.9383          | 0.185    | 0.8742     | 6.0724 | 0.185    | 0.0488   | 0.2474 | 0.7712 |
| No log        | 10.96 | 33   | 3.9336          | 0.185    | 0.8746     | 6.7953 | 0.185    | 0.0488   | 0.2533 | 0.7685 |
| No log        | 11.96 | 36   | 3.9298          | 0.185    | 0.8755     | 6.9469 | 0.185    | 0.0488   | 0.2679 | 0.7659 |
| No log        | 12.96 | 39   | 3.9253          | 0.185    | 0.8756     | 6.9654 | 0.185    | 0.0488   | 0.2591 | 0.7640 |
| No log        | 13.96 | 42   | 3.9194          | 0.185    | 0.8750     | 6.9522 | 0.185    | 0.0488   | 0.2681 | 0.7604 |
| No log        | 14.96 | 45   | 3.9128          | 0.185    | 0.8744     | 6.9200 | 0.185    | 0.0488   | 0.2611 | 0.7617 |
| No log        | 15.96 | 48   | 3.9074          | 0.185    | 0.8733     | 6.8369 | 0.185    | 0.0488   | 0.2611 | 0.7600 |
| No log        | 16.96 | 51   | 3.9041          | 0.185    | 0.8726     | 6.8278 | 0.185    | 0.0488   | 0.2558 | 0.7566 |
| No log        | 17.96 | 54   | 3.9025          | 0.185    | 0.8719     | 6.7039 | 0.185    | 0.0488   | 0.2588 | 0.7510 |
| No log        | 18.96 | 57   | 3.9012          | 0.185    | 0.8717     | 6.6384 | 0.185    | 0.0488   | 0.2580 | 0.7484 |
| No log        | 19.96 | 60   | 3.8987          | 0.185    | 0.8712     | 6.6323 | 0.185    | 0.0488   | 0.2612 | 0.7450 |
| No log        | 20.96 | 63   | 3.8971          | 0.185    | 0.8712     | 6.6319 | 0.185    | 0.0488   | 0.2615 | 0.7443 |
| No log        | 21.96 | 66   | 3.8956          | 0.185    | 0.8710     | 6.6323 | 0.185    | 0.0488   | 0.2659 | 0.7439 |
| No log        | 22.96 | 69   | 3.8945          | 0.185    | 0.8708     | 6.6307 | 0.185    | 0.0488   | 0.2569 | 0.7436 |
| No log        | 23.96 | 72   | 3.8940          | 0.185    | 0.8708     | 6.6295 | 0.185    | 0.0488   | 0.2526 | 0.7434 |
| No log        | 24.96 | 75   | 3.8936          | 0.185    | 0.8707     | 6.6284 | 0.185    | 0.0488   | 0.2527 | 0.7434 |


### Framework versions

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

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