---
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: pogny_10_32_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/8upm8cw9)
# pogny_10_32_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: 1.6859
- 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: 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 2.8512        | 1.0   | 2409  | 3.1877          | 0.4376   | 0.2665 |
| 2.7295        | 2.0   | 4818  | 3.5982          | 0.0702   | 0.0092 |
| 2.5873        | 3.0   | 7227  | 1.9106          | 0.4376   | 0.2665 |
| 2.3248        | 4.0   | 9636  | 2.4274          | 0.4376   | 0.2665 |
| 2.2087        | 5.0   | 12045 | 2.0673          | 0.2545   | 0.1032 |
| 2.17          | 6.0   | 14454 | 2.3342          | 0.4376   | 0.2665 |
| 2.0611        | 7.0   | 16863 | 1.9937          | 0.4376   | 0.2665 |
| 1.8834        | 8.0   | 19272 | 1.8107          | 0.4376   | 0.2665 |
| 1.7959        | 9.0   | 21681 | 1.7571          | 0.4376   | 0.2665 |
| 1.7009        | 10.0  | 24090 | 1.6859          | 0.4376   | 0.2665 |


### Framework versions

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