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# dit-tiny_tobacco3482_kd_CEKD_t2.5_a0.5

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: 3.9560
- Accuracy: 0.18
- Brier Loss: 0.8800
- Nll: 6.8606
- F1 Micro: 0.18
- F1 Macro: 0.0306
- Ece: 0.2612
- Aurc: 0.8512

## 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    | 4.2281          | 0.145    | 0.8999     | 10.1620 | 0.145    | 0.0253   | 0.2222 | 0.8467 |
| No log        | 1.96  | 6    | 4.1872          | 0.145    | 0.8946     | 10.5915 | 0.145    | 0.0253   | 0.2275 | 0.8468 |
| No log        | 2.96  | 9    | 4.1248          | 0.155    | 0.8866     | 8.6280  | 0.155    | 0.0360   | 0.2179 | 0.8487 |
| No log        | 3.96  | 12   | 4.0716          | 0.155    | 0.8806     | 6.5480  | 0.155    | 0.0272   | 0.2254 | 0.8851 |
| No log        | 4.96  | 15   | 4.0359          | 0.155    | 0.8778     | 6.7781  | 0.155    | 0.0271   | 0.2310 | 0.8931 |
| No log        | 5.96  | 18   | 4.0135          | 0.155    | 0.8774     | 7.8547  | 0.155    | 0.0271   | 0.2345 | 0.8965 |
| No log        | 6.96  | 21   | 3.9978          | 0.185    | 0.8779     | 8.3528  | 0.185    | 0.0468   | 0.2615 | 0.8612 |
| No log        | 7.96  | 24   | 3.9867          | 0.18     | 0.8789     | 7.6001  | 0.18     | 0.0308   | 0.2618 | 0.8546 |
| No log        | 8.96  | 27   | 3.9782          | 0.18     | 0.8796     | 7.0871  | 0.18     | 0.0306   | 0.2613 | 0.8538 |
| No log        | 9.96  | 30   | 3.9726          | 0.18     | 0.8800     | 7.0519  | 0.18     | 0.0306   | 0.2687 | 0.8545 |
| No log        | 10.96 | 33   | 3.9684          | 0.18     | 0.8803     | 7.0277  | 0.18     | 0.0306   | 0.2656 | 0.8537 |
| No log        | 11.96 | 36   | 3.9654          | 0.18     | 0.8805     | 7.0162  | 0.18     | 0.0306   | 0.2708 | 0.8536 |
| No log        | 12.96 | 39   | 3.9633          | 0.18     | 0.8805     | 7.0056  | 0.18     | 0.0306   | 0.2619 | 0.8535 |
| No log        | 13.96 | 42   | 3.9614          | 0.18     | 0.8804     | 6.9981  | 0.18     | 0.0306   | 0.2617 | 0.8532 |
| No log        | 14.96 | 45   | 3.9598          | 0.18     | 0.8804     | 6.9923  | 0.18     | 0.0306   | 0.2669 | 0.8531 |
| No log        | 15.96 | 48   | 3.9586          | 0.18     | 0.8803     | 6.9334  | 0.18     | 0.0306   | 0.2669 | 0.8529 |
| No log        | 16.96 | 51   | 3.9578          | 0.18     | 0.8802     | 6.9237  | 0.18     | 0.0306   | 0.2716 | 0.8522 |
| No log        | 17.96 | 54   | 3.9576          | 0.18     | 0.8802     | 6.8704  | 0.18     | 0.0306   | 0.2666 | 0.8521 |
| No log        | 18.96 | 57   | 3.9574          | 0.18     | 0.8802     | 6.8662  | 0.18     | 0.0306   | 0.2664 | 0.8523 |
| No log        | 19.96 | 60   | 3.9568          | 0.18     | 0.8801     | 6.8641  | 0.18     | 0.0306   | 0.2614 | 0.8518 |
| No log        | 20.96 | 63   | 3.9566          | 0.18     | 0.8801     | 6.8634  | 0.18     | 0.0306   | 0.2659 | 0.8516 |
| No log        | 21.96 | 66   | 3.9563          | 0.18     | 0.8800     | 6.8632  | 0.18     | 0.0306   | 0.2612 | 0.8516 |
| No log        | 22.96 | 69   | 3.9561          | 0.18     | 0.8800     | 6.8620  | 0.18     | 0.0306   | 0.2612 | 0.8513 |
| No log        | 23.96 | 72   | 3.9561          | 0.18     | 0.8800     | 6.8611  | 0.18     | 0.0306   | 0.2612 | 0.8513 |
| No log        | 24.96 | 75   | 3.9560          | 0.18     | 0.8800     | 6.8606  | 0.18     | 0.0306   | 0.2612 | 0.8512 |


### Framework versions

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

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