Downloads · 30 days
10
2% of all-time downloads
klue_ynat_roberta_base_model
chunwoolee0/klue_ynat_roberta_base_model
klue_ynat_roberta_base_model is a text classification model from chunwoolee0. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
459
Public
Repo size
2.7 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin443 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Jul 18, 2023
- Updated
- Sep 12, 2023
- SHA
- fb5847e7
Try a prompt
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
klue_ynat_roberta_base_model
This model is a fine-tuned version of klue/roberta-base on the klue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3747
- F1: 0.8720
Model description
Pretrained RoBERTa Model on Korean Language. See Github and Paper for more details.
Intended uses & limitations
Pretrained RoBERTa Model on Korean Language. See Github and Paper for more details.
Training and evaluation data
How to use
NOTE: Use BertTokenizer instead of RobertaTokenizer. (AutoTokenizer will load BertTokenizer)
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("klue/roberta-base")
tokenizer = AutoTokenizer.from_pretrained("klue/roberta-base")
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 179 | 0.4838 | 0.8444 |
| No log | 2.0 | 358 | 0.3848 | 0.8659 |
| 0.4203 | 3.0 | 537 | 0.3778 | 0.8690 |
| 0.4203 | 4.0 | 716 | 0.3762 | 0.8702 |
| 0.4203 | 5.0 | 895 | 0.3747 | 0.8720 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Jul 18, 2023
- Updated
- Sep 12, 2023