---
base_model: klue/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-interview-intent-f
  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-interview-intent-f

This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9555
- Accuracy: 0.6763
- Macro F1: 0.4521
- Weighted F1: 0.6773

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 1.4857        | 1.0   | 859  | 1.4013          | 0.6564   | 0.3414   | 0.6440      |
| 0.6763        | 2.0   | 1718 | 1.3329          | 0.6673   | 0.4038   | 0.6551      |
| 0.4559        | 3.0   | 2577 | 1.4175          | 0.6654   | 0.4042   | 0.6653      |
| 0.2971        | 4.0   | 3436 | 1.5689          | 0.6622   | 0.4170   | 0.6637      |
| 0.1885        | 5.0   | 4295 | 1.6916          | 0.6656   | 0.4249   | 0.6694      |
| 0.1181        | 6.0   | 5154 | 1.8043          | 0.6763   | 0.4374   | 0.6713      |
| 0.0677        | 7.0   | 6013 | 1.9043          | 0.6736   | 0.4415   | 0.6756      |
| 0.0404        | 8.0   | 6872 | 1.9555          | 0.6763   | 0.4521   | 0.6773      |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.8.0+cu128
- Datasets 2.19.0
- Tokenizers 0.19.1