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# dit-tiny_tobacco3482_kd_CEKD_t2.5_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: 3.2510
- Accuracy: 0.18
- Brier Loss: 0.8767
- Nll: 6.8039
- F1 Micro: 0.18
- F1 Macro: 0.0306
- Ece: 0.2513
- Aurc: 0.8508

## 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    | 3.4586          | 0.145    | 0.8999     | 10.1587 | 0.145    | 0.0253   | 0.2221 | 0.8467 |
| No log        | 1.96  | 6    | 3.4232          | 0.145    | 0.8946     | 10.5824 | 0.145    | 0.0253   | 0.2242 | 0.8475 |
| No log        | 2.96  | 9    | 3.3704          | 0.16     | 0.8867     | 8.6135  | 0.16     | 0.0503   | 0.2171 | 0.8440 |
| No log        | 3.96  | 12   | 3.3273          | 0.155    | 0.8807     | 6.5471  | 0.155    | 0.0274   | 0.2248 | 0.8831 |
| No log        | 4.96  | 15   | 3.3006          | 0.155    | 0.8779     | 6.8045  | 0.155    | 0.0271   | 0.2331 | 0.8918 |
| No log        | 5.96  | 18   | 3.2856          | 0.16     | 0.8773     | 8.2046  | 0.16     | 0.0329   | 0.2361 | 0.8956 |
| No log        | 6.96  | 21   | 3.2758          | 0.18     | 0.8774     | 8.0738  | 0.18     | 0.0308   | 0.2561 | 0.8544 |
| No log        | 7.96  | 24   | 3.2688          | 0.18     | 0.8778     | 7.1046  | 0.18     | 0.0308   | 0.2647 | 0.8524 |
| No log        | 8.96  | 27   | 3.2630          | 0.18     | 0.8778     | 6.9910  | 0.18     | 0.0306   | 0.2591 | 0.8530 |
| No log        | 9.96  | 30   | 3.2597          | 0.18     | 0.8778     | 6.9680  | 0.18     | 0.0306   | 0.2736 | 0.8538 |
| No log        | 10.96 | 33   | 3.2573          | 0.18     | 0.8776     | 6.9547  | 0.18     | 0.0306   | 0.2698 | 0.8536 |
| No log        | 11.96 | 36   | 3.2557          | 0.18     | 0.8775     | 6.9491  | 0.18     | 0.0306   | 0.2653 | 0.8533 |
| No log        | 12.96 | 39   | 3.2546          | 0.18     | 0.8773     | 6.8987  | 0.18     | 0.0306   | 0.2606 | 0.8526 |
| No log        | 13.96 | 42   | 3.2536          | 0.18     | 0.8771     | 6.8204  | 0.18     | 0.0306   | 0.2601 | 0.8523 |
| No log        | 14.96 | 45   | 3.2528          | 0.18     | 0.8771     | 6.8141  | 0.18     | 0.0306   | 0.2521 | 0.8519 |
| No log        | 15.96 | 48   | 3.2522          | 0.18     | 0.8769     | 6.8074  | 0.18     | 0.0306   | 0.2606 | 0.8517 |
| No log        | 16.96 | 51   | 3.2519          | 0.18     | 0.8769     | 6.8077  | 0.18     | 0.0306   | 0.2607 | 0.8515 |
| No log        | 17.96 | 54   | 3.2520          | 0.18     | 0.8769     | 6.8050  | 0.18     | 0.0306   | 0.2561 | 0.8510 |
| No log        | 18.96 | 57   | 3.2520          | 0.18     | 0.8769     | 6.8057  | 0.18     | 0.0306   | 0.2519 | 0.8509 |
| No log        | 19.96 | 60   | 3.2515          | 0.18     | 0.8768     | 6.8046  | 0.18     | 0.0306   | 0.2556 | 0.8507 |
| No log        | 20.96 | 63   | 3.2514          | 0.18     | 0.8768     | 6.8048  | 0.18     | 0.0306   | 0.2515 | 0.8506 |
| No log        | 21.96 | 66   | 3.2512          | 0.18     | 0.8767     | 6.8048  | 0.18     | 0.0306   | 0.2556 | 0.8508 |
| No log        | 22.96 | 69   | 3.2510          | 0.18     | 0.8767     | 6.8045  | 0.18     | 0.0306   | 0.2513 | 0.8509 |
| No log        | 23.96 | 72   | 3.2510          | 0.18     | 0.8767     | 6.8043  | 0.18     | 0.0306   | 0.2513 | 0.8508 |
| No log        | 24.96 | 75   | 3.2510          | 0.18     | 0.8767     | 6.8039  | 0.18     | 0.0306   | 0.2513 | 0.8508 |


### Framework versions

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

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