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# dit-small_tobacco3482_kd_CEKD_t1.5_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: 2.2890
- Accuracy: 0.19
- Brier Loss: 0.8648
- Nll: 6.4150
- F1 Micro: 0.19
- F1 Macro: 0.0641
- Ece: 0.2450
- Aurc: 0.7332

## 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    | 2.4806          | 0.06     | 0.9041     | 9.2838 | 0.06     | 0.0114   | 0.1750 | 0.9034 |
| No log        | 1.96  | 6    | 2.4041          | 0.18     | 0.8884     | 6.3227 | 0.18     | 0.0305   | 0.2317 | 0.8027 |
| No log        | 2.96  | 9    | 2.3381          | 0.18     | 0.8760     | 6.9952 | 0.18     | 0.0305   | 0.2424 | 0.8118 |
| No log        | 3.96  | 12   | 2.3362          | 0.185    | 0.8771     | 6.9040 | 0.185    | 0.0488   | 0.2544 | 0.7841 |
| No log        | 4.96  | 15   | 2.3345          | 0.185    | 0.8747     | 6.8515 | 0.185    | 0.0488   | 0.2476 | 0.7768 |
| No log        | 5.96  | 18   | 2.3339          | 0.185    | 0.8725     | 6.0111 | 0.185    | 0.0490   | 0.2457 | 0.7670 |
| No log        | 6.96  | 21   | 2.3348          | 0.185    | 0.8718     | 5.9199 | 0.185    | 0.0488   | 0.2328 | 0.7596 |
| No log        | 7.96  | 24   | 2.3310          | 0.185    | 0.8711     | 5.9008 | 0.185    | 0.0488   | 0.2443 | 0.7536 |
| No log        | 8.96  | 27   | 2.3231          | 0.185    | 0.8699     | 5.8793 | 0.185    | 0.0488   | 0.2337 | 0.7516 |
| No log        | 9.96  | 30   | 2.3181          | 0.185    | 0.8694     | 6.6980 | 0.185    | 0.0488   | 0.2507 | 0.7500 |
| No log        | 10.96 | 33   | 2.3139          | 0.185    | 0.8692     | 6.7350 | 0.185    | 0.0488   | 0.2481 | 0.7488 |
| No log        | 11.96 | 36   | 2.3099          | 0.185    | 0.8690     | 6.7557 | 0.185    | 0.0488   | 0.2484 | 0.7463 |
| No log        | 12.96 | 39   | 2.3057          | 0.185    | 0.8684     | 6.6765 | 0.185    | 0.0488   | 0.2598 | 0.7441 |
| No log        | 13.96 | 42   | 2.3014          | 0.185    | 0.8676     | 6.6313 | 0.185    | 0.0488   | 0.2478 | 0.7420 |
| No log        | 14.96 | 45   | 2.2978          | 0.185    | 0.8669     | 6.6142 | 0.185    | 0.0488   | 0.2496 | 0.7412 |
| No log        | 15.96 | 48   | 2.2955          | 0.185    | 0.8664     | 6.5990 | 0.185    | 0.0488   | 0.2379 | 0.7399 |
| No log        | 16.96 | 51   | 2.2947          | 0.185    | 0.8662     | 6.4895 | 0.185    | 0.0488   | 0.2452 | 0.7375 |
| No log        | 17.96 | 54   | 2.2949          | 0.185    | 0.8661     | 6.4730 | 0.185    | 0.0488   | 0.2438 | 0.7354 |
| No log        | 18.96 | 57   | 2.2949          | 0.185    | 0.8661     | 6.4244 | 0.185    | 0.0488   | 0.2435 | 0.7356 |
| No log        | 19.96 | 60   | 2.2930          | 0.185    | 0.8657     | 6.3676 | 0.185    | 0.0490   | 0.2389 | 0.7341 |
| No log        | 20.96 | 63   | 2.2918          | 0.19     | 0.8654     | 6.4233 | 0.19     | 0.0641   | 0.2446 | 0.7336 |
| No log        | 21.96 | 66   | 2.2905          | 0.19     | 0.8651     | 6.4742 | 0.19     | 0.0641   | 0.2485 | 0.7334 |
| No log        | 22.96 | 69   | 2.2897          | 0.19     | 0.8649     | 6.4243 | 0.19     | 0.0641   | 0.2448 | 0.7332 |
| No log        | 23.96 | 72   | 2.2893          | 0.19     | 0.8648     | 6.4174 | 0.19     | 0.0641   | 0.2450 | 0.7332 |
| No log        | 24.96 | 75   | 2.2890          | 0.19     | 0.8648     | 6.4150 | 0.19     | 0.0641   | 0.2450 | 0.7332 |


### Framework versions

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

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