Downloads · 30 days
5
6% of all-time downloads
RoBERTa-CyNER
Cyber-ThreaD/RoBERTa-CyNER
RoBERTa-CyNER is a token classification model from Cyber-ThreaD. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
77
Public
Parameters
124M
496 MB on disk
Likes
1
Public
Repo makeup
Click a slice to open those files.
.safetensors496 MB · 99%
At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Dec 6, 2023
- Updated
- Dec 6, 2023
- SHA
- be243c73
Try a prompt
Base models
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. -->
dnrti_our
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0737
- Precision: 0.7870
- Recall: 0.7880
- F1: 0.7875
- Accuracy: 0.9836
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.13 | 1.42 | 500 | 0.0886 | 0.7138 | 0.7548 | 0.7337 | 0.9796 |
| 0.0421 | 2.84 | 1000 | 0.0737 | 0.7870 | 0.7880 | 0.7875 | 0.9836 |
| 0.0249 | 4.26 | 1500 | 0.0855 | 0.7655 | 0.7714 | 0.7684 | 0.9822 |
| 0.0167 | 5.68 | 2000 | 0.0946 | 0.7554 | 0.8008 | 0.7774 | 0.9826 |
| 0.0104 | 7.1 | 2500 | 0.0976 | 0.7540 | 0.7829 | 0.7682 | 0.9820 |
| 0.0066 | 8.52 | 3000 | 0.1024 | 0.7742 | 0.8059 | 0.7897 | 0.9836 |
| 0.0044 | 9.94 | 3500 | 0.1069 | 0.7764 | 0.7982 | 0.7872 | 0.9833 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Token Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Dec 6, 2023
- Updated
- Dec 6, 2023