metadata
base_model: klue/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-interview-intent
results: []
roberta-interview-intent
This model is a fine-tuned version of 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