Downloads · 30 days
6
1% of all-time downloads
vit_for_dfl
ManuD/vit_for_dfl
vit_for_dfl is a image classification model from ManuD. 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
632
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
- Jan 3, 2023
- Updated
- Jan 3, 2023
- SHA
- 4f1baed9
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. -->
vit_for_dfl
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the dfl dataset. It achieves the following results on the evaluation set:
- Loss: 0.1771
- F1: 0.2453
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.0836 | 1.0 | 358 | 0.1841 | 0.2453 |
| 0.207 | 2.0 | 716 | 0.1835 | 0.2453 |
| 0.2325 | 3.0 | 1074 | 0.1771 | 0.2453 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jan 3, 2023
- Updated
- Jan 3, 2023