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---
metrics:
- f1
- accuracy
model-index:
- name: aha_class
  results: []
---

<!-- 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. -->

# aha_class

This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0885
- F1: 0.9580
- Roc Auc: 0.9679
- Accuracy: 0.9391

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 42   | 0.1723          | 0.95   | 0.9635  | 0.9217   |
| No log        | 2.0   | 84   | 0.1160          | 0.9576 | 0.9659  | 0.9391   |
| No log        | 3.0   | 126  | 0.1064          | 0.9492 | 0.9595  | 0.9304   |
| No log        | 4.0   | 168  | 0.0974          | 0.9540 | 0.9657  | 0.9304   |
| No log        | 5.0   | 210  | 0.0968          | 0.9580 | 0.9679  | 0.9304   |
| No log        | 6.0   | 252  | 0.0885          | 0.9580 | 0.9679  | 0.9391   |
| No log        | 7.0   | 294  | 0.1005          | 0.9580 | 0.9679  | 0.9391   |
| No log        | 8.0   | 336  | 0.0921          | 0.9664 | 0.9743  | 0.9478   |
| No log        | 9.0   | 378  | 0.1055          | 0.9580 | 0.9679  | 0.9391   |
| No log        | 10.0  | 420  | 0.0988          | 0.9664 | 0.9743  | 0.9478   |
| No log        | 11.0  | 462  | 0.0993          | 0.9664 | 0.9743  | 0.9478   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1