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# dit-tiny_tobacco3482_kd_MSE

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: 6.8328
- Accuracy: 0.19
- Brier Loss: 0.8942
- Nll: 7.0296
- F1 Micro: 0.19
- F1 Macro: 0.0703
- Ece: 0.2429
- Aurc: 0.8146

## 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    | 7.1188          | 0.145    | 0.9003     | 10.1627 | 0.145    | 0.0253   | 0.2218 | 0.8463 |
| No log        | 1.96  | 6    | 7.0608          | 0.145    | 0.8969     | 9.8809  | 0.145    | 0.0253   | 0.2197 | 0.8454 |
| No log        | 2.96  | 9    | 6.9777          | 0.145    | 0.8929     | 8.9712  | 0.145    | 0.0442   | 0.2065 | 0.7921 |
| No log        | 3.96  | 12   | 6.9144          | 0.17     | 0.8908     | 4.9924  | 0.17     | 0.0413   | 0.2325 | 0.7807 |
| No log        | 4.96  | 15   | 6.8797          | 0.145    | 0.8912     | 6.8983  | 0.145    | 0.0399   | 0.2089 | 0.7932 |
| No log        | 5.96  | 18   | 6.8636          | 0.085    | 0.8926     | 6.9917  | 0.085    | 0.0299   | 0.1822 | 0.8755 |
| No log        | 6.96  | 21   | 6.8545          | 0.075    | 0.8946     | 7.0604  | 0.075    | 0.0307   | 0.1849 | 0.8758 |
| No log        | 7.96  | 24   | 6.8486          | 0.06     | 0.8958     | 7.1035  | 0.06     | 0.0230   | 0.1801 | 0.8891 |
| No log        | 8.96  | 27   | 6.8455          | 0.165    | 0.8967     | 7.1315  | 0.165    | 0.0604   | 0.2414 | 0.8438 |
| No log        | 9.96  | 30   | 6.8450          | 0.185    | 0.8973     | 7.1546  | 0.185    | 0.0468   | 0.2477 | 0.8436 |
| No log        | 10.96 | 33   | 6.8438          | 0.18     | 0.8969     | 7.1569  | 0.18     | 0.0308   | 0.2406 | 0.8504 |
| No log        | 11.96 | 36   | 6.8414          | 0.18     | 0.8962     | 7.1492  | 0.18     | 0.0306   | 0.2510 | 0.8501 |
| No log        | 12.96 | 39   | 6.8390          | 0.18     | 0.8958     | 7.1455  | 0.18     | 0.0306   | 0.2374 | 0.8494 |
| No log        | 13.96 | 42   | 6.8365          | 0.18     | 0.8950     | 7.0793  | 0.18     | 0.0306   | 0.2436 | 0.8488 |
| No log        | 14.96 | 45   | 6.8349          | 0.18     | 0.8944     | 7.0591  | 0.18     | 0.0306   | 0.2369 | 0.8486 |
| No log        | 15.96 | 48   | 6.8338          | 0.18     | 0.8942     | 7.0493  | 0.18     | 0.0306   | 0.2396 | 0.8482 |
| No log        | 16.96 | 51   | 6.8335          | 0.18     | 0.8940     | 7.0429  | 0.18     | 0.0309   | 0.2390 | 0.8486 |
| No log        | 17.96 | 54   | 6.8341          | 0.18     | 0.8943     | 7.0410  | 0.18     | 0.0314   | 0.2351 | 0.8514 |
| No log        | 18.96 | 57   | 6.8338          | 0.19     | 0.8943     | 7.0391  | 0.19     | 0.0495   | 0.2480 | 0.8471 |
| No log        | 19.96 | 60   | 6.8335          | 0.205    | 0.8943     | 7.0342  | 0.205    | 0.0722   | 0.2562 | 0.8204 |
| No log        | 20.96 | 63   | 6.8334          | 0.2      | 0.8942     | 7.0308  | 0.2000   | 0.0683   | 0.2541 | 0.8199 |
| No log        | 21.96 | 66   | 6.8332          | 0.195    | 0.8942     | 7.0296  | 0.195    | 0.0714   | 0.2511 | 0.8099 |
| No log        | 22.96 | 69   | 6.8330          | 0.195    | 0.8942     | 7.0297  | 0.195    | 0.0717   | 0.2572 | 0.8123 |
| No log        | 23.96 | 72   | 6.8329          | 0.19     | 0.8942     | 7.0294  | 0.19     | 0.0703   | 0.2459 | 0.8148 |
| No log        | 24.96 | 75   | 6.8328          | 0.19     | 0.8942     | 7.0296  | 0.19     | 0.0703   | 0.2429 | 0.8146 |


### Framework versions

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

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