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# dit-tiny_tobacco3482_kd_CEKD_t1.5_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: 2.6280
- Accuracy: 0.18
- Brier Loss: 0.8747
- Nll: 6.7569
- F1 Micro: 0.18
- F1 Macro: 0.0306
- Ece: 0.2550
- Aurc: 0.8496

## 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    | 2.7961          | 0.145    | 0.8999     | 10.1560 | 0.145    | 0.0253   | 0.2221 | 0.8467 |
| No log        | 1.96  | 6    | 2.7646          | 0.145    | 0.8946     | 10.5828 | 0.145    | 0.0253   | 0.2242 | 0.8475 |
| No log        | 2.96  | 9    | 2.7185          | 0.155    | 0.8868     | 8.6137  | 0.155    | 0.0501   | 0.2145 | 0.8394 |
| No log        | 3.96  | 12   | 2.6825          | 0.21     | 0.8808     | 6.5439  | 0.2100   | 0.0613   | 0.2567 | 0.8351 |
| No log        | 4.96  | 15   | 2.6619          | 0.155    | 0.8778     | 6.7839  | 0.155    | 0.0274   | 0.2346 | 0.8880 |
| No log        | 5.96  | 18   | 2.6517          | 0.18     | 0.8769     | 7.4578  | 0.18     | 0.0395   | 0.2461 | 0.8571 |
| No log        | 6.96  | 21   | 2.6450          | 0.18     | 0.8767     | 7.1192  | 0.18     | 0.0308   | 0.2518 | 0.8516 |
| No log        | 7.96  | 24   | 2.6400          | 0.18     | 0.8766     | 6.9539  | 0.18     | 0.0306   | 0.2472 | 0.8526 |
| No log        | 8.96  | 27   | 2.6355          | 0.18     | 0.8762     | 6.9109  | 0.18     | 0.0306   | 0.2524 | 0.8527 |
| No log        | 9.96  | 30   | 2.6332          | 0.18     | 0.8759     | 6.8997  | 0.18     | 0.0306   | 0.2491 | 0.8527 |
| No log        | 10.96 | 33   | 2.6317          | 0.18     | 0.8757     | 6.8943  | 0.18     | 0.0306   | 0.2529 | 0.8524 |
| No log        | 11.96 | 36   | 2.6309          | 0.18     | 0.8755     | 6.8287  | 0.18     | 0.0306   | 0.2442 | 0.8523 |
| No log        | 12.96 | 39   | 2.6304          | 0.18     | 0.8753     | 6.7670  | 0.18     | 0.0306   | 0.2478 | 0.8521 |
| No log        | 13.96 | 42   | 2.6298          | 0.18     | 0.8752     | 6.7597  | 0.18     | 0.0306   | 0.2433 | 0.8517 |
| No log        | 14.96 | 45   | 2.6293          | 0.18     | 0.8751     | 6.7590  | 0.18     | 0.0306   | 0.2516 | 0.8513 |
| No log        | 15.96 | 48   | 2.6290          | 0.18     | 0.8750     | 6.7556  | 0.18     | 0.0306   | 0.2555 | 0.8515 |
| No log        | 16.96 | 51   | 2.6287          | 0.18     | 0.8750     | 6.7582  | 0.18     | 0.0306   | 0.2557 | 0.8514 |
| No log        | 17.96 | 54   | 2.6289          | 0.18     | 0.8750     | 6.7556  | 0.18     | 0.0306   | 0.2476 | 0.8509 |
| No log        | 18.96 | 57   | 2.6289          | 0.18     | 0.8750     | 6.7567  | 0.18     | 0.0306   | 0.2475 | 0.8505 |
| No log        | 19.96 | 60   | 2.6285          | 0.18     | 0.8748     | 6.7567  | 0.18     | 0.0306   | 0.2433 | 0.8502 |
| No log        | 20.96 | 63   | 2.6283          | 0.18     | 0.8748     | 6.7577  | 0.18     | 0.0306   | 0.2512 | 0.8500 |
| No log        | 21.96 | 66   | 2.6281          | 0.18     | 0.8748     | 6.7586  | 0.18     | 0.0306   | 0.2551 | 0.8495 |
| No log        | 22.96 | 69   | 2.6280          | 0.18     | 0.8747     | 6.7580  | 0.18     | 0.0306   | 0.2550 | 0.8496 |
| No log        | 23.96 | 72   | 2.6280          | 0.18     | 0.8747     | 6.7573  | 0.18     | 0.0306   | 0.2550 | 0.8496 |
| No log        | 24.96 | 75   | 2.6280          | 0.18     | 0.8747     | 6.7569  | 0.18     | 0.0306   | 0.2550 | 0.8496 |


### Framework versions

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

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