metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: hana-64-0.005
results: []
hana-64-0.005
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: 1.9708
- Accuracy: 0.3096
- F1: 0.1463
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: 0.005
- 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 |
|---|---|---|---|---|---|
| 2.2731 | 1.0 | 1097 | 2.2254 | 0.3096 | 0.1463 |
| 2.1577 | 2.0 | 2194 | 2.2213 | 0.2034 | 0.0687 |
| 2.04 | 3.0 | 3291 | 1.9708 | 0.3096 | 0.1463 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.2
- Datasets 2.19.1
- Tokenizers 0.19.1