---
base_model: klue/roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: roberta-base-finetuned-ynat
  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. -->

# roberta-base-finetuned-ynat

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: 0.3938
- F1: 0.8672

## 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: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3162        | 0.56  | 50   | 0.4069          | 0.8610 |
| 0.276         | 1.11  | 100  | 0.4176          | 0.8587 |
| 0.2706        | 1.67  | 150  | 0.4036          | 0.8631 |
| 0.2941        | 2.22  | 200  | 0.4232          | 0.8590 |
| 0.2778        | 2.78  | 250  | 0.3994          | 0.8623 |
| 0.2575        | 3.33  | 300  | 0.3979          | 0.8628 |
| 0.2389        | 3.89  | 350  | 0.4008          | 0.8652 |
| 0.2258        | 4.44  | 400  | 0.3950          | 0.8653 |
| 0.2097        | 5.0   | 450  | 0.3938          | 0.8672 |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0