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# dit-tiny_tobacco3482_kd_CEKD_t5.0_a0.7

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: 3.1844
- Accuracy: 0.18
- Brier Loss: 0.8763
- Nll: 6.0873
- F1 Micro: 0.18
- F1 Macro: 0.0306
- Ece: 0.2492
- Aurc: 0.8505

## 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    | 3.3625          | 0.145    | 0.8999     | 10.1577 | 0.145    | 0.0253   | 0.2220 | 0.8466 |
| No log        | 1.96  | 6    | 3.3300          | 0.145    | 0.8947     | 10.5652 | 0.145    | 0.0253   | 0.2237 | 0.8468 |
| No log        | 2.96  | 9    | 3.2822          | 0.14     | 0.8870     | 8.5877  | 0.14     | 0.0453   | 0.2040 | 0.8325 |
| No log        | 3.96  | 12   | 3.2442          | 0.16     | 0.8812     | 6.5385  | 0.16     | 0.0327   | 0.2208 | 0.8814 |
| No log        | 4.96  | 15   | 3.2219          | 0.155    | 0.8784     | 7.1527  | 0.155    | 0.0271   | 0.2352 | 0.8898 |
| No log        | 5.96  | 18   | 3.2105          | 0.185    | 0.8778     | 8.7319  | 0.185    | 0.0517   | 0.2548 | 0.8944 |
| No log        | 6.96  | 21   | 3.2032          | 0.18     | 0.8778     | 8.8034  | 0.18     | 0.0308   | 0.2478 | 0.8527 |
| No log        | 7.96  | 24   | 3.1980          | 0.18     | 0.8779     | 8.1814  | 0.18     | 0.0306   | 0.2635 | 0.8527 |
| No log        | 8.96  | 27   | 3.1937          | 0.18     | 0.8777     | 7.0314  | 0.18     | 0.0306   | 0.2618 | 0.8529 |
| No log        | 9.96  | 30   | 3.1915          | 0.18     | 0.8776     | 6.9166  | 0.18     | 0.0306   | 0.2591 | 0.8537 |
| No log        | 10.96 | 33   | 3.1900          | 0.18     | 0.8774     | 6.8864  | 0.18     | 0.0306   | 0.2551 | 0.8535 |
| No log        | 11.96 | 36   | 3.1889          | 0.18     | 0.8773     | 6.5148  | 0.18     | 0.0306   | 0.2547 | 0.8532 |
| No log        | 12.96 | 39   | 3.1881          | 0.18     | 0.8771     | 6.1469  | 0.18     | 0.0306   | 0.2543 | 0.8530 |
| No log        | 13.96 | 42   | 3.1872          | 0.18     | 0.8769     | 6.1318  | 0.18     | 0.0306   | 0.2538 | 0.8525 |
| No log        | 14.96 | 45   | 3.1865          | 0.18     | 0.8768     | 6.0783  | 0.18     | 0.0306   | 0.2501 | 0.8525 |
| No log        | 15.96 | 48   | 3.1859          | 0.18     | 0.8766     | 6.0654  | 0.18     | 0.0306   | 0.2500 | 0.8520 |
| No log        | 16.96 | 51   | 3.1855          | 0.18     | 0.8766     | 6.0809  | 0.18     | 0.0306   | 0.2459 | 0.8516 |
| No log        | 17.96 | 54   | 3.1855          | 0.18     | 0.8766     | 6.0610  | 0.18     | 0.0306   | 0.2497 | 0.8515 |
| No log        | 18.96 | 57   | 3.1854          | 0.18     | 0.8766     | 6.0659  | 0.18     | 0.0306   | 0.2579 | 0.8515 |
| No log        | 19.96 | 60   | 3.1850          | 0.18     | 0.8764     | 6.0737  | 0.18     | 0.0306   | 0.2656 | 0.8513 |
| No log        | 20.96 | 63   | 3.1848          | 0.18     | 0.8764     | 6.0869  | 0.18     | 0.0306   | 0.2575 | 0.8510 |
| No log        | 21.96 | 66   | 3.1846          | 0.18     | 0.8764     | 6.1423  | 0.18     | 0.0306   | 0.2533 | 0.8510 |
| No log        | 22.96 | 69   | 3.1845          | 0.18     | 0.8763     | 6.1047  | 0.18     | 0.0306   | 0.2532 | 0.8505 |
| No log        | 23.96 | 72   | 3.1845          | 0.18     | 0.8763     | 6.0895  | 0.18     | 0.0306   | 0.2532 | 0.8504 |
| No log        | 24.96 | 75   | 3.1844          | 0.18     | 0.8763     | 6.0873  | 0.18     | 0.0306   | 0.2492 | 0.8505 |


### Framework versions

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

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