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# dit-tiny_tobacco3482_kd_CEKD_t5.0_a0.9

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: 2.5147
- Accuracy: 0.18
- Brier Loss: 0.8746
- Nll: 6.7241
- F1 Micro: 0.18
- F1 Macro: 0.0306
- Ece: 0.2451
- Aurc: 0.8494

## 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    | 2.6571          | 0.145    | 0.8999     | 10.1542 | 0.145    | 0.0253   | 0.2220 | 0.8466 |
| No log        | 1.96  | 6    | 2.6281          | 0.145    | 0.8947     | 10.5635 | 0.145    | 0.0253   | 0.2236 | 0.8461 |
| No log        | 2.96  | 9    | 2.5865          | 0.14     | 0.8870     | 8.5822  | 0.14     | 0.0433   | 0.2063 | 0.8040 |
| No log        | 3.96  | 12   | 2.5552          | 0.19     | 0.8811     | 6.5445  | 0.19     | 0.0552   | 0.2421 | 0.8576 |
| No log        | 4.96  | 15   | 2.5387          | 0.155    | 0.8782     | 7.1184  | 0.155    | 0.0277   | 0.2280 | 0.8892 |
| No log        | 5.96  | 18   | 2.5317          | 0.18     | 0.8774     | 8.7285  | 0.18     | 0.0319   | 0.2392 | 0.8538 |
| No log        | 6.96  | 21   | 2.5274          | 0.18     | 0.8770     | 8.2533  | 0.18     | 0.0306   | 0.2476 | 0.8514 |
| No log        | 7.96  | 24   | 2.5238          | 0.18     | 0.8767     | 6.9903  | 0.18     | 0.0306   | 0.2465 | 0.8523 |
| No log        | 8.96  | 27   | 2.5205          | 0.18     | 0.8762     | 6.9049  | 0.18     | 0.0306   | 0.2473 | 0.8528 |
| No log        | 9.96  | 30   | 2.5189          | 0.18     | 0.8758     | 6.8830  | 0.18     | 0.0306   | 0.2515 | 0.8526 |
| No log        | 10.96 | 33   | 2.5180          | 0.18     | 0.8756     | 6.8133  | 0.18     | 0.0306   | 0.2469 | 0.8522 |
| No log        | 11.96 | 36   | 2.5175          | 0.18     | 0.8754     | 6.7422  | 0.18     | 0.0306   | 0.2500 | 0.8519 |
| No log        | 12.96 | 39   | 2.5173          | 0.18     | 0.8753     | 6.5762  | 0.18     | 0.0306   | 0.2533 | 0.8515 |
| No log        | 13.96 | 42   | 2.5168          | 0.18     | 0.8751     | 6.5666  | 0.18     | 0.0306   | 0.2528 | 0.8516 |
| No log        | 14.96 | 45   | 2.5164          | 0.18     | 0.8750     | 6.7246  | 0.18     | 0.0306   | 0.2532 | 0.8512 |
| No log        | 15.96 | 48   | 2.5160          | 0.18     | 0.8750     | 6.7221  | 0.18     | 0.0306   | 0.2456 | 0.8507 |
| No log        | 16.96 | 51   | 2.5157          | 0.18     | 0.8749     | 6.7242  | 0.18     | 0.0306   | 0.2457 | 0.8507 |
| No log        | 17.96 | 54   | 2.5158          | 0.18     | 0.8749     | 6.7241  | 0.18     | 0.0306   | 0.2417 | 0.8503 |
| No log        | 18.96 | 57   | 2.5157          | 0.18     | 0.8749     | 6.7259  | 0.18     | 0.0306   | 0.2455 | 0.8503 |
| No log        | 19.96 | 60   | 2.5153          | 0.18     | 0.8748     | 6.7248  | 0.18     | 0.0306   | 0.2452 | 0.8495 |
| No log        | 20.96 | 63   | 2.5151          | 0.18     | 0.8748     | 6.7250  | 0.18     | 0.0306   | 0.2414 | 0.8494 |
| No log        | 21.96 | 66   | 2.5149          | 0.18     | 0.8747     | 6.7250  | 0.18     | 0.0306   | 0.2452 | 0.8495 |
| No log        | 22.96 | 69   | 2.5147          | 0.18     | 0.8747     | 6.7247  | 0.18     | 0.0306   | 0.2451 | 0.8495 |
| No log        | 23.96 | 72   | 2.5147          | 0.18     | 0.8747     | 6.7246  | 0.18     | 0.0306   | 0.2451 | 0.8495 |
| No log        | 24.96 | 75   | 2.5147          | 0.18     | 0.8746     | 6.7241  | 0.18     | 0.0306   | 0.2451 | 0.8494 |


### Framework versions

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

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