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

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: 1.8618
- Accuracy: 0.6771
- Macro F1: 0.4469
- Weighted F1: 0.6798

## 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: 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 1.8294        | 1.0   | 859  | 1.4177          | 0.6630   | 0.3062   | 0.6381      |
| 0.7746        | 2.0   | 1718 | 1.3270          | 0.6777   | 0.3558   | 0.6590      |
| 0.5419        | 3.0   | 2577 | 1.3263          | 0.6806   | 0.4224   | 0.6715      |
| 0.3855        | 4.0   | 3436 | 1.4520          | 0.6775   | 0.4342   | 0.6726      |
| 0.2805        | 5.0   | 4295 | 1.5418          | 0.6775   | 0.4364   | 0.6767      |
| 0.2026        | 6.0   | 5154 | 1.5926          | 0.6734   | 0.4439   | 0.6771      |
| 0.1448        | 7.0   | 6013 | 1.7215          | 0.6775   | 0.4451   | 0.6802      |
| 0.106         | 8.0   | 6872 | 1.8030          | 0.6728   | 0.4492   | 0.6781      |
| 0.0778        | 9.0   | 7731 | 1.8198          | 0.6806   | 0.4518   | 0.6828      |
| 0.0611        | 10.0  | 8590 | 1.8618          | 0.6771   | 0.4469   | 0.6798      |


### Framework versions

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