metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: hana-64-0.00002
results: []
hana-64-0.00002
This model is a fine-tuned version of klue/roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3992
- Accuracy: 0.7137
- F1: 0.7114
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2557 | 1.0 | 1097 | 1.1509 | 0.7130 | 0.7101 |
| 0.1925 | 2.0 | 2194 | 1.2460 | 0.7094 | 0.7082 |
| 0.117 | 3.0 | 3291 | 1.3992 | 0.7137 | 0.7114 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.2
- Datasets 2.19.1
- Tokenizers 0.19.1