
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# dit-small_tobacco3482_kd_CEKD_t2.5_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: 3.1993
- Accuracy: 0.185
- Brier Loss: 0.8672
- Nll: 6.5703
- F1 Micro: 0.185
- F1 Macro: 0.0488
- Ece: 0.2594
- Aurc: 0.7367

## 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    | 3.4684          | 0.06     | 0.9042     | 9.2910 | 0.06     | 0.0114   | 0.1755 | 0.9033 |
| No log        | 1.96  | 6    | 3.3741          | 0.18     | 0.8886     | 6.5491 | 0.18     | 0.0305   | 0.2324 | 0.8055 |
| No log        | 2.96  | 9    | 3.2779          | 0.18     | 0.8767     | 7.2662 | 0.18     | 0.0305   | 0.2493 | 0.8196 |
| No log        | 3.96  | 12   | 3.2605          | 0.18     | 0.8816     | 7.0963 | 0.18     | 0.0305   | 0.2628 | 0.8140 |
| No log        | 4.96  | 15   | 3.2592          | 0.185    | 0.8814     | 6.9350 | 0.185    | 0.0488   | 0.2584 | 0.7850 |
| No log        | 5.96  | 18   | 3.2576          | 0.185    | 0.8782     | 6.3113 | 0.185    | 0.0488   | 0.2561 | 0.7731 |
| No log        | 6.96  | 21   | 3.2540          | 0.185    | 0.8747     | 6.0058 | 0.185    | 0.0488   | 0.2446 | 0.7705 |
| No log        | 7.96  | 24   | 3.2500          | 0.185    | 0.8731     | 5.9849 | 0.185    | 0.0488   | 0.2442 | 0.7669 |
| No log        | 8.96  | 27   | 3.2430          | 0.185    | 0.8717     | 5.9785 | 0.185    | 0.0488   | 0.2483 | 0.7626 |
| No log        | 9.96  | 30   | 3.2377          | 0.185    | 0.8711     | 6.2837 | 0.185    | 0.0488   | 0.2462 | 0.7609 |
| No log        | 10.96 | 33   | 3.2332          | 0.185    | 0.8713     | 6.8641 | 0.185    | 0.0488   | 0.2560 | 0.7601 |
| No log        | 11.96 | 36   | 3.2293          | 0.185    | 0.8719     | 6.8631 | 0.185    | 0.0488   | 0.2523 | 0.7587 |
| No log        | 12.96 | 39   | 3.2246          | 0.185    | 0.8717     | 6.8535 | 0.185    | 0.0488   | 0.2526 | 0.7558 |
| No log        | 13.96 | 42   | 3.2190          | 0.185    | 0.8709     | 6.8177 | 0.185    | 0.0488   | 0.2565 | 0.7533 |
| No log        | 14.96 | 45   | 3.2134          | 0.185    | 0.8700     | 6.7894 | 0.185    | 0.0488   | 0.2630 | 0.7533 |
| No log        | 15.96 | 48   | 3.2091          | 0.185    | 0.8691     | 6.7672 | 0.185    | 0.0488   | 0.2585 | 0.7500 |
| No log        | 16.96 | 51   | 3.2069          | 0.185    | 0.8687     | 6.6512 | 0.185    | 0.0488   | 0.2536 | 0.7466 |
| No log        | 17.96 | 54   | 3.2063          | 0.185    | 0.8682     | 6.5227 | 0.185    | 0.0488   | 0.2520 | 0.7429 |
| No log        | 18.96 | 57   | 3.2057          | 0.185    | 0.8682     | 6.5119 | 0.185    | 0.0488   | 0.2514 | 0.7406 |
| No log        | 19.96 | 60   | 3.2036          | 0.185    | 0.8678     | 6.5674 | 0.185    | 0.0488   | 0.2501 | 0.7385 |
| No log        | 20.96 | 63   | 3.2023          | 0.185    | 0.8677     | 6.5709 | 0.185    | 0.0488   | 0.2506 | 0.7385 |
| No log        | 21.96 | 66   | 3.2010          | 0.185    | 0.8675     | 6.5731 | 0.185    | 0.0488   | 0.2631 | 0.7376 |
| No log        | 22.96 | 69   | 3.2000          | 0.185    | 0.8673     | 6.5723 | 0.185    | 0.0488   | 0.2591 | 0.7371 |
| No log        | 23.96 | 72   | 3.1996          | 0.185    | 0.8673     | 6.5715 | 0.185    | 0.0488   | 0.2593 | 0.7368 |
| No log        | 24.96 | 75   | 3.1993          | 0.185    | 0.8672     | 6.5703 | 0.185    | 0.0488   | 0.2594 | 0.7367 |


### Framework versions

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

adve email form letter memo news note report resume scientific