---
base_model: klue/roberta-small
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: sentence_classification
  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. -->

# sentence_classification

This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0744
- Precision: 0.9707
- Recall: 0.97
- F1: 0.9698
- Accuracy: 0.97

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 18   | 0.1791          | 0.9524    | 0.95   | 0.9497 | 0.95     |
| No log        | 2.0   | 36   | 0.0987          | 0.9707    | 0.97   | 0.9698 | 0.97     |
| No log        | 3.0   | 54   | 0.0958          | 0.9808    | 0.98   | 0.9800 | 0.98     |
| No log        | 4.0   | 72   | 0.0839          | 0.9808    | 0.98   | 0.9797 | 0.98     |
| No log        | 5.0   | 90   | 0.0744          | 0.9707    | 0.97   | 0.9698 | 0.97     |
| No log        | 6.0   | 108  | 0.0793          | 0.9707    | 0.97   | 0.9698 | 0.97     |


### Framework versions

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