---
library_name: transformers
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: mbti-ei-classifier
  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. -->

# mbti-ei-classifier

This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6583
- Accuracy: 0.6375
- F1: 0.7786
- Precision: 0.6375
- Recall: 1.0

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6637        | 1.0   | 1164 | 0.6543          | 0.6429   | 0.7826 | 0.6429    | 1.0    |
| 0.6691        | 2.0   | 2328 | 0.6616          | 0.6429   | 0.7826 | 0.6429    | 1.0    |
| 0.6552        | 3.0   | 3492 | 0.6598          | 0.6429   | 0.7826 | 0.6429    | 1.0    |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.2
- Tokenizers 0.22.1