Downloads · 30 days
11
38% of all-time downloads
ft-bert-base-uncased-for-binary-search
ncminhieu/ft-bert-base-uncased-for-binary-search
ft-bert-base-uncased-for-binary-search is a text classification model from ncminhieu. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
29
Public
Parameters
109M
1.8 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors438 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Nov 9, 2024
- Updated
- Nov 9, 2024
- SHA
- effdd4b5
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. -->
ft-bert-base-uncased-for-binary-search
This model is a fine-tuned version of bert-base-uncased on the https://www.kaggle.com/datasets/skywardai/network-vulnerability-fixed dataset. It achieves the following results on the evaluation set:
- Loss: 0.3218
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|
| 0.2419 | 1.0 | 50 | 0.3060 |
| 0.3139 | 2.0 | 100 | 0.3275 |
| 0.198 | 3.0 | 150 | 0.3218 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Nov 9, 2024
- Updated
- Nov 9, 2024