
<!-- 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_simkd_CEKD_t1_aNone

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: 0.9983
- Accuracy: 0.18
- Brier Loss: 0.8965
- Nll: 6.7849
- F1 Micro: 0.18
- F1 Macro: 0.0305
- Ece: 0.2195
- Aurc: 0.8182

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- 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  | 12   | 1.0062          | 0.18     | 0.8980     | 6.1518 | 0.18     | 0.0309   | 0.2213 | 0.7838 |
| No log        | 1.96  | 24   | 1.0034          | 0.18     | 0.8987     | 5.7795 | 0.18     | 0.0305   | 0.2273 | 0.8165 |
| No log        | 2.96  | 36   | 1.0025          | 0.18     | 0.8984     | 6.4819 | 0.18     | 0.0305   | 0.2249 | 0.8306 |
| No log        | 3.96  | 48   | 1.0018          | 0.18     | 0.8982     | 6.8521 | 0.18     | 0.0306   | 0.2205 | 0.8505 |
| No log        | 4.96  | 60   | 1.0015          | 0.16     | 0.8980     | 6.6853 | 0.16     | 0.0324   | 0.2089 | 0.8798 |
| No log        | 5.96  | 72   | 1.0011          | 0.175    | 0.8979     | 6.8349 | 0.175    | 0.0314   | 0.2134 | 0.8345 |
| No log        | 6.96  | 84   | 1.0008          | 0.18     | 0.8976     | 6.8293 | 0.18     | 0.0313   | 0.2249 | 0.8208 |
| No log        | 7.96  | 96   | 1.0005          | 0.18     | 0.8975     | 6.9400 | 0.18     | 0.0305   | 0.2230 | 0.8140 |
| No log        | 8.96  | 108  | 1.0003          | 0.18     | 0.8974     | 6.5877 | 0.18     | 0.0306   | 0.2230 | 0.8246 |
| No log        | 9.96  | 120  | 1.0000          | 0.18     | 0.8973     | 6.5454 | 0.18     | 0.0306   | 0.2188 | 0.8188 |
| No log        | 10.96 | 132  | 0.9998          | 0.18     | 0.8972     | 6.5555 | 0.18     | 0.0306   | 0.2274 | 0.8151 |
| No log        | 11.96 | 144  | 0.9996          | 0.18     | 0.8971     | 6.5819 | 0.18     | 0.0306   | 0.2254 | 0.8131 |
| No log        | 12.96 | 156  | 0.9994          | 0.18     | 0.8970     | 6.7150 | 0.18     | 0.0305   | 0.2255 | 0.8162 |
| No log        | 13.96 | 168  | 0.9993          | 0.18     | 0.8969     | 6.6542 | 0.18     | 0.0305   | 0.2213 | 0.8220 |
| No log        | 14.96 | 180  | 0.9991          | 0.18     | 0.8968     | 6.6025 | 0.18     | 0.0305   | 0.2213 | 0.8125 |
| No log        | 15.96 | 192  | 0.9990          | 0.18     | 0.8968     | 7.0424 | 0.18     | 0.0305   | 0.2301 | 0.8201 |
| No log        | 16.96 | 204  | 0.9988          | 0.18     | 0.8967     | 6.6676 | 0.18     | 0.0305   | 0.2258 | 0.8153 |
| No log        | 17.96 | 216  | 0.9987          | 0.18     | 0.8967     | 6.6621 | 0.18     | 0.0305   | 0.2270 | 0.8145 |
| No log        | 18.96 | 228  | 0.9986          | 0.18     | 0.8967     | 7.0058 | 0.18     | 0.0305   | 0.2259 | 0.8214 |
| No log        | 19.96 | 240  | 0.9985          | 0.18     | 0.8966     | 6.8777 | 0.18     | 0.0305   | 0.2194 | 0.8183 |
| No log        | 20.96 | 252  | 0.9984          | 0.18     | 0.8966     | 6.7612 | 0.18     | 0.0305   | 0.2282 | 0.8131 |
| No log        | 21.96 | 264  | 0.9984          | 0.18     | 0.8966     | 6.7811 | 0.18     | 0.0305   | 0.2282 | 0.8145 |
| No log        | 22.96 | 276  | 0.9983          | 0.18     | 0.8965     | 6.7044 | 0.18     | 0.0305   | 0.2239 | 0.8167 |
| No log        | 23.96 | 288  | 0.9983          | 0.18     | 0.8965     | 6.7813 | 0.18     | 0.0305   | 0.2217 | 0.8183 |
| No log        | 24.96 | 300  | 0.9983          | 0.18     | 0.8965     | 6.7849 | 0.18     | 0.0305   | 0.2195 | 0.8182 |


### 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