Downloads · 30 days
5
1% of all-time downloads
vit-base-molecul
dyvapandhu/vit-base-molecul
vit-base-molecul is a image classification model from dyvapandhu. Use it when you need a label for an image. 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
504
Public
Repo size
1 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin343 MB · 100%
At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Jul 18, 2023
- Updated
- Jul 19, 2023
- SHA
- 3e35957a
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. -->
vit-base-molecul
This model is a fine-tuned version of google/vit-base-patch16-224 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6052
- Accuracy: 0.69
- F1: 0.6900
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: 32
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4633 | 3.85 | 50 | 0.6052 | 0.69 | 0.6900 |
| 0.0341 | 7.69 | 100 | 0.8705 | 0.71 | 0.7100 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1
- Datasets 2.13.1
- Tokenizers 0.11.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jul 18, 2023
- Updated
- Jul 19, 2023