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# dit-small_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: 3.1347
- Accuracy: 0.185
- Brier Loss: 0.8666
- Nll: 5.9997
- F1 Micro: 0.185
- F1 Macro: 0.0488
- Ece: 0.2480
- Aurc: 0.7353

## 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    | 3.3695          | 0.06     | 0.9042     | 9.1505 | 0.06     | 0.0114   | 0.1750 | 0.9033 |
| No log        | 1.96  | 6    | 3.2847          | 0.18     | 0.8890     | 7.1646 | 0.18     | 0.0305   | 0.2263 | 0.8027 |
| No log        | 2.96  | 9    | 3.2039          | 0.18     | 0.8773     | 8.6118 | 0.18     | 0.0305   | 0.2478 | 0.8186 |
| No log        | 3.96  | 12   | 3.1950          | 0.18     | 0.8806     | 7.4891 | 0.18     | 0.0305   | 0.2514 | 0.8131 |
| No log        | 4.96  | 15   | 3.1951          | 0.185    | 0.8795     | 6.7125 | 0.185    | 0.0488   | 0.2555 | 0.7835 |
| No log        | 5.96  | 18   | 3.1931          | 0.185    | 0.8766     | 5.2600 | 0.185    | 0.0488   | 0.2526 | 0.7702 |
| No log        | 6.96  | 21   | 3.1876          | 0.185    | 0.8741     | 5.6453 | 0.185    | 0.0488   | 0.2372 | 0.7672 |
| No log        | 7.96  | 24   | 3.1800          | 0.185    | 0.8726     | 5.9473 | 0.185    | 0.0488   | 0.2412 | 0.7644 |
| No log        | 8.96  | 27   | 3.1712          | 0.185    | 0.8712     | 5.9421 | 0.185    | 0.0488   | 0.2491 | 0.7615 |
| No log        | 9.96  | 30   | 3.1656          | 0.185    | 0.8704     | 6.6276 | 0.185    | 0.0488   | 0.2516 | 0.7602 |
| No log        | 10.96 | 33   | 3.1623          | 0.185    | 0.8704     | 6.8796 | 0.185    | 0.0488   | 0.2487 | 0.7598 |
| No log        | 11.96 | 36   | 3.1601          | 0.185    | 0.8708     | 7.1352 | 0.185    | 0.0488   | 0.2451 | 0.7559 |
| No log        | 12.96 | 39   | 3.1573          | 0.185    | 0.8706     | 7.0151 | 0.185    | 0.0488   | 0.2492 | 0.7531 |
| No log        | 13.96 | 42   | 3.1531          | 0.185    | 0.8699     | 6.7912 | 0.185    | 0.0488   | 0.2450 | 0.7484 |
| No log        | 14.96 | 45   | 3.1485          | 0.185    | 0.8693     | 6.6578 | 0.185    | 0.0488   | 0.2513 | 0.7491 |
| No log        | 15.96 | 48   | 3.1449          | 0.185    | 0.8685     | 6.1407 | 0.185    | 0.0488   | 0.2596 | 0.7463 |
| No log        | 16.96 | 51   | 3.1428          | 0.185    | 0.8681     | 5.9160 | 0.185    | 0.0488   | 0.2548 | 0.7432 |
| No log        | 17.96 | 54   | 3.1421          | 0.185    | 0.8678     | 5.8419 | 0.185    | 0.0488   | 0.2449 | 0.7401 |
| No log        | 18.96 | 57   | 3.1413          | 0.185    | 0.8677     | 5.7417 | 0.185    | 0.0488   | 0.2606 | 0.7382 |
| No log        | 19.96 | 60   | 3.1391          | 0.185    | 0.8673     | 5.7824 | 0.185    | 0.0488   | 0.2432 | 0.7365 |
| No log        | 20.96 | 63   | 3.1378          | 0.185    | 0.8671     | 5.9509 | 0.185    | 0.0488   | 0.2598 | 0.7368 |
| No log        | 21.96 | 66   | 3.1364          | 0.185    | 0.8668     | 6.0164 | 0.185    | 0.0488   | 0.2477 | 0.7361 |
| No log        | 22.96 | 69   | 3.1355          | 0.185    | 0.8667     | 6.0109 | 0.185    | 0.0488   | 0.2437 | 0.7352 |
| No log        | 23.96 | 72   | 3.1350          | 0.185    | 0.8666     | 6.0029 | 0.185    | 0.0488   | 0.2438 | 0.7351 |
| No log        | 24.96 | 75   | 3.1347          | 0.185    | 0.8666     | 5.9997 | 0.185    | 0.0488   | 0.2480 | 0.7353 |


### Framework versions

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

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