---
base_model: klue/roberta-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mainCut-label9
  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. -->

# mainCut-label9

This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1075
- Accuracy: 0.6309

## 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: 5e-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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2286        | 0.4   | 500  | 1.2054          | 0.5685   |
| 1.2387        | 0.8   | 1000 | 1.1320          | 0.6062   |
| 0.9892        | 1.2   | 1500 | 1.1341          | 0.6169   |
| 1.1259        | 1.6   | 2000 | 1.1117          | 0.6202   |
| 0.9904        | 2.0   | 2500 | 1.0929          | 0.6262   |
| 1.0053        | 2.4   | 3000 | 1.1021          | 0.6243   |
| 0.9492        | 2.8   | 3500 | 1.0982          | 0.6251   |
| 0.9811        | 3.2   | 4000 | 1.1167          | 0.6238   |
| 0.9258        | 3.6   | 4500 | 1.1068          | 0.6341   |
| 0.8481        | 4.0   | 5000 | 1.1075          | 0.6309   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3