
<!-- 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-tiny_tobacco3482_kd_CEKD_t2.5_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: 2.5379
- Accuracy: 0.18
- Brier Loss: 0.8746
- Nll: 6.7389
- F1 Micro: 0.18
- F1 Macro: 0.0306
- Ece: 0.2460
- Aurc: 0.8496

## 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    | 2.6891          | 0.145    | 0.8999     | 10.1550 | 0.145    | 0.0253   | 0.2220 | 0.8466 |
| No log        | 1.96  | 6    | 2.6592          | 0.145    | 0.8947     | 10.5706 | 0.145    | 0.0253   | 0.2238 | 0.8463 |
| No log        | 2.96  | 9    | 2.6158          | 0.14     | 0.8869     | 8.5528  | 0.14     | 0.0422   | 0.2066 | 0.8175 |
| No log        | 3.96  | 12   | 2.5827          | 0.175    | 0.8810     | 6.5464  | 0.175    | 0.0467   | 0.2385 | 0.8661 |
| No log        | 4.96  | 15   | 2.5647          | 0.155    | 0.8781     | 6.8570  | 0.155    | 0.0274   | 0.2316 | 0.8886 |
| No log        | 5.96  | 18   | 2.5566          | 0.19     | 0.8772     | 8.4283  | 0.19     | 0.0413   | 0.2460 | 0.8532 |
| No log        | 6.96  | 21   | 2.5515          | 0.18     | 0.8769     | 7.6865  | 0.18     | 0.0308   | 0.2480 | 0.8517 |
| No log        | 7.96  | 24   | 2.5475          | 0.18     | 0.8767     | 6.9727  | 0.18     | 0.0306   | 0.2469 | 0.8521 |
| No log        | 8.96  | 27   | 2.5438          | 0.18     | 0.8762     | 6.9080  | 0.18     | 0.0306   | 0.2438 | 0.8525 |
| No log        | 9.96  | 30   | 2.5420          | 0.18     | 0.8758     | 6.8906  | 0.18     | 0.0306   | 0.2521 | 0.8528 |
| No log        | 10.96 | 33   | 2.5410          | 0.18     | 0.8755     | 6.8317  | 0.18     | 0.0306   | 0.2516 | 0.8524 |
| No log        | 11.96 | 36   | 2.5404          | 0.18     | 0.8753     | 6.7606  | 0.18     | 0.0306   | 0.2469 | 0.8516 |
| No log        | 12.96 | 39   | 2.5401          | 0.18     | 0.8752     | 6.7444  | 0.18     | 0.0306   | 0.2425 | 0.8516 |
| No log        | 13.96 | 42   | 2.5397          | 0.18     | 0.8751     | 6.7397  | 0.18     | 0.0306   | 0.2498 | 0.8514 |
| No log        | 14.96 | 45   | 2.5393          | 0.18     | 0.8750     | 6.7390  | 0.18     | 0.0306   | 0.2579 | 0.8511 |
| No log        | 15.96 | 48   | 2.5389          | 0.18     | 0.8749     | 6.7366  | 0.18     | 0.0306   | 0.2463 | 0.8513 |
| No log        | 16.96 | 51   | 2.5387          | 0.18     | 0.8749     | 6.7390  | 0.18     | 0.0306   | 0.2465 | 0.8510 |
| No log        | 17.96 | 54   | 2.5389          | 0.18     | 0.8749     | 6.7382  | 0.18     | 0.0306   | 0.2425 | 0.8505 |
| No log        | 18.96 | 57   | 2.5389          | 0.18     | 0.8749     | 6.7397  | 0.18     | 0.0306   | 0.2463 | 0.8504 |
| No log        | 19.96 | 60   | 2.5384          | 0.18     | 0.8748     | 6.7391  | 0.18     | 0.0306   | 0.2421 | 0.8495 |
| No log        | 20.96 | 63   | 2.5383          | 0.18     | 0.8747     | 6.7396  | 0.18     | 0.0306   | 0.2422 | 0.8500 |
| No log        | 21.96 | 66   | 2.5380          | 0.18     | 0.8747     | 6.7399  | 0.18     | 0.0306   | 0.2460 | 0.8496 |
| No log        | 22.96 | 69   | 2.5379          | 0.18     | 0.8746     | 6.7395  | 0.18     | 0.0306   | 0.2460 | 0.8497 |
| No log        | 23.96 | 72   | 2.5379          | 0.18     | 0.8746     | 6.7393  | 0.18     | 0.0306   | 0.2460 | 0.8497 |
| No log        | 24.96 | 75   | 2.5379          | 0.18     | 0.8746     | 6.7389  | 0.18     | 0.0306   | 0.2460 | 0.8496 |


### 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