---
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: pogny_10_64_0.01
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/bella05/huggingface/runs/2fqy4l1d)
# pogny_10_64_0.01

This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6851
- Accuracy: 0.4376
- F1: 0.2665

## 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: 0.01
- 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 2.491         | 1.0   | 1205  | 2.5033          | 0.4376   | 0.2665 |
| 2.4679        | 2.0   | 2410  | 1.9460          | 0.4376   | 0.2665 |
| 2.302         | 3.0   | 3615  | 2.4098          | 0.0702   | 0.0092 |
| 2.1762        | 4.0   | 4820  | 2.2698          | 0.0545   | 0.0056 |
| 2.0639        | 5.0   | 6025  | 1.9917          | 0.4376   | 0.2665 |
| 2.0031        | 6.0   | 7230  | 1.9130          | 0.4376   | 0.2665 |
| 1.9241        | 7.0   | 8435  | 2.0131          | 0.4376   | 0.2665 |
| 1.8227        | 8.0   | 9640  | 1.8212          | 0.4376   | 0.2665 |
| 1.7854        | 9.0   | 10845 | 1.7379          | 0.4376   | 0.2665 |
| 1.7037        | 10.0  | 12050 | 1.6851          | 0.4376   | 0.2665 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.2.2
- Datasets 2.19.1
- Tokenizers 0.19.1