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# dit-tiny_tobacco3482_kd_CEKD_t2.0_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: 3.5976
- Accuracy: 0.18
- Brier Loss: 0.8781
- Nll: 6.8947
- F1 Micro: 0.18
- F1 Macro: 0.0306
- Ece: 0.2499
- Aurc: 0.8510

## 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    | 3.8479          | 0.145    | 0.8999     | 10.1604 | 0.145    | 0.0253   | 0.2222 | 0.8467 |
| No log        | 1.96  | 6    | 3.8090          | 0.145    | 0.8946     | 10.5967 | 0.145    | 0.0253   | 0.2246 | 0.8470 |
| No log        | 2.96  | 9    | 3.7500          | 0.16     | 0.8866     | 8.6365  | 0.16     | 0.0406   | 0.2205 | 0.8486 |
| No log        | 3.96  | 12   | 3.7003          | 0.16     | 0.8805     | 6.5484  | 0.16     | 0.0327   | 0.2242 | 0.8816 |
| No log        | 4.96  | 15   | 3.6677          | 0.155    | 0.8776     | 6.7592  | 0.155    | 0.0271   | 0.2365 | 0.8919 |
| No log        | 5.96  | 18   | 3.6477          | 0.155    | 0.8770     | 7.2639  | 0.155    | 0.0278   | 0.2368 | 0.8961 |
| No log        | 6.96  | 21   | 3.6339          | 0.18     | 0.8774     | 7.3546  | 0.18     | 0.0313   | 0.2486 | 0.8556 |
| No log        | 7.96  | 24   | 3.6240          | 0.18     | 0.8781     | 7.0685  | 0.18     | 0.0308   | 0.2654 | 0.8528 |
| No log        | 8.96  | 27   | 3.6163          | 0.18     | 0.8784     | 7.0041  | 0.18     | 0.0306   | 0.2561 | 0.8532 |
| No log        | 9.96  | 30   | 3.6114          | 0.18     | 0.8787     | 6.9904  | 0.18     | 0.0306   | 0.2584 | 0.8537 |
| No log        | 10.96 | 33   | 3.6078          | 0.18     | 0.8788     | 6.9806  | 0.18     | 0.0306   | 0.2594 | 0.8538 |
| No log        | 11.96 | 36   | 3.6052          | 0.18     | 0.8789     | 6.9768  | 0.18     | 0.0306   | 0.2596 | 0.8537 |
| No log        | 12.96 | 39   | 3.6034          | 0.18     | 0.8788     | 6.9716  | 0.18     | 0.0306   | 0.2507 | 0.8532 |
| No log        | 13.96 | 42   | 3.6018          | 0.18     | 0.8786     | 6.9683  | 0.18     | 0.0306   | 0.2548 | 0.8527 |
| No log        | 14.96 | 45   | 3.6005          | 0.18     | 0.8786     | 6.9040  | 0.18     | 0.0306   | 0.2597 | 0.8524 |
| No log        | 15.96 | 48   | 3.5995          | 0.18     | 0.8784     | 6.8978  | 0.18     | 0.0306   | 0.2685 | 0.8518 |
| No log        | 16.96 | 51   | 3.5989          | 0.18     | 0.8784     | 6.8972  | 0.18     | 0.0306   | 0.2641 | 0.8515 |
| No log        | 17.96 | 54   | 3.5989          | 0.18     | 0.8784     | 6.8961  | 0.18     | 0.0306   | 0.2550 | 0.8513 |
| No log        | 18.96 | 57   | 3.5988          | 0.18     | 0.8784     | 6.8968  | 0.18     | 0.0306   | 0.2505 | 0.8510 |
| No log        | 19.96 | 60   | 3.5982          | 0.18     | 0.8782     | 6.8956  | 0.18     | 0.0306   | 0.2478 | 0.8511 |
| No log        | 20.96 | 63   | 3.5980          | 0.18     | 0.8782     | 6.8954  | 0.18     | 0.0306   | 0.2456 | 0.8507 |
| No log        | 21.96 | 66   | 3.5978          | 0.18     | 0.8782     | 6.8951  | 0.18     | 0.0306   | 0.2499 | 0.8511 |
| No log        | 22.96 | 69   | 3.5976          | 0.18     | 0.8781     | 6.8949  | 0.18     | 0.0306   | 0.2499 | 0.8510 |
| No log        | 23.96 | 72   | 3.5976          | 0.18     | 0.8781     | 6.8949  | 0.18     | 0.0306   | 0.2499 | 0.8510 |
| No log        | 24.96 | 75   | 3.5976          | 0.18     | 0.8781     | 6.8947  | 0.18     | 0.0306   | 0.2499 | 0.8510 |


### Framework versions

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

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