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# dit-small_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: 2.4735
- Accuracy: 0.19
- Brier Loss: 0.8651
- Nll: 6.3618
- F1 Micro: 0.19
- F1 Macro: 0.0641
- Ece: 0.2456
- Aurc: 0.7331

## 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    | 2.6674          | 0.06     | 0.9042     | 9.2824 | 0.06     | 0.0114   | 0.1749 | 0.9042 |
| No log        | 1.96  | 6    | 2.5911          | 0.18     | 0.8886     | 6.4746 | 0.18     | 0.0305   | 0.2317 | 0.8026 |
| No log        | 2.96  | 9    | 2.5252          | 0.18     | 0.8764     | 7.5079 | 0.18     | 0.0305   | 0.2390 | 0.8141 |
| No log        | 3.96  | 12   | 2.5235          | 0.185    | 0.8777     | 6.9489 | 0.185    | 0.0488   | 0.2553 | 0.7838 |
| No log        | 4.96  | 15   | 2.5223          | 0.185    | 0.8754     | 6.8606 | 0.185    | 0.0488   | 0.2572 | 0.7773 |
| No log        | 5.96  | 18   | 2.5213          | 0.185    | 0.8732     | 5.9794 | 0.185    | 0.0488   | 0.2384 | 0.7684 |
| No log        | 6.96  | 21   | 2.5203          | 0.185    | 0.8723     | 5.9244 | 0.185    | 0.0488   | 0.2406 | 0.7603 |
| No log        | 7.96  | 24   | 2.5149          | 0.185    | 0.8713     | 5.9034 | 0.185    | 0.0488   | 0.2484 | 0.7560 |
| No log        | 8.96  | 27   | 2.5064          | 0.185    | 0.8701     | 5.9325 | 0.185    | 0.0488   | 0.2525 | 0.7529 |
| No log        | 9.96  | 30   | 2.5014          | 0.185    | 0.8695     | 6.7123 | 0.185    | 0.0488   | 0.2399 | 0.7528 |
| No log        | 10.96 | 33   | 2.4977          | 0.185    | 0.8693     | 6.7598 | 0.185    | 0.0488   | 0.2487 | 0.7511 |
| No log        | 11.96 | 36   | 2.4944          | 0.185    | 0.8692     | 6.8130 | 0.185    | 0.0488   | 0.2488 | 0.7476 |
| No log        | 12.96 | 39   | 2.4908          | 0.185    | 0.8688     | 6.7610 | 0.185    | 0.0488   | 0.2488 | 0.7452 |
| No log        | 13.96 | 42   | 2.4867          | 0.185    | 0.8680     | 6.6686 | 0.185    | 0.0488   | 0.2484 | 0.7428 |
| No log        | 14.96 | 45   | 2.4830          | 0.185    | 0.8673     | 6.6283 | 0.185    | 0.0488   | 0.2426 | 0.7431 |
| No log        | 15.96 | 48   | 2.4805          | 0.185    | 0.8668     | 6.4857 | 0.185    | 0.0488   | 0.2385 | 0.7410 |
| No log        | 16.96 | 51   | 2.4794          | 0.185    | 0.8666     | 6.4425 | 0.185    | 0.0488   | 0.2459 | 0.7385 |
| No log        | 17.96 | 54   | 2.4795          | 0.185    | 0.8664     | 6.0769 | 0.185    | 0.0488   | 0.2406 | 0.7352 |
| No log        | 18.96 | 57   | 2.4793          | 0.185    | 0.8664     | 6.1000 | 0.185    | 0.0488   | 0.2402 | 0.7355 |
| No log        | 19.96 | 60   | 2.4774          | 0.185    | 0.8660     | 6.3802 | 0.185    | 0.0488   | 0.2506 | 0.7346 |
| No log        | 20.96 | 63   | 2.4762          | 0.185    | 0.8657     | 6.4330 | 0.185    | 0.0488   | 0.2550 | 0.7344 |
| No log        | 21.96 | 66   | 2.4750          | 0.185    | 0.8654     | 6.3721 | 0.185    | 0.0488   | 0.2513 | 0.7333 |
| No log        | 22.96 | 69   | 2.4741          | 0.19     | 0.8652     | 6.3676 | 0.19     | 0.0641   | 0.2453 | 0.7332 |
| No log        | 23.96 | 72   | 2.4738          | 0.19     | 0.8652     | 6.3645 | 0.19     | 0.0641   | 0.2455 | 0.7331 |
| No log        | 24.96 | 75   | 2.4735          | 0.19     | 0.8651     | 6.3618 | 0.19     | 0.0641   | 0.2456 | 0.7331 |


### Framework versions

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

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