Downloads · 30 days
16
3% of all-time downloads
finetuned-classficatin-fer2013
AutumnQiu/finetuned-classficatin-fer2013
finetuned-classficatin-fer2013 is a image classification model from AutumnQiu. 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
470
Public
Repo size
687 MB
Likes
1
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
- Dec 28, 2023
- Updated
- Dec 28, 2023
- SHA
- 09d28ae0
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. -->
finetuned-classficatin-fer2013
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the fer2013 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0586
- Accuracy: 0.6952
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5814 | 0.06 | 100 | 1.1124 | 0.6525 |
| 0.3856 | 0.11 | 200 | 1.1988 | 0.6428 |
| 0.4073 | 0.17 | 300 | 1.2319 | 0.6492 |
| 0.3408 | 0.22 | 400 | 1.1527 | 0.6581 |
| 0.4001 | 0.28 | 500 | 1.1861 | 0.6601 |
| 0.3973 | 0.33 | 600 | 1.1161 | 0.6637 |
| 0.3897 | 0.39 | 700 | 1.2955 | 0.6464 |
| 0.4689 | 0.45 | 800 | 1.1492 | 0.6578 |
| 0.4173 | 0.5 | 900 | 1.1538 | 0.6659 |
| 0.3238 | 0.56 | 1000 | 1.1742 | 0.6704 |
| 0.2774 | 0.61 | 1100 | 1.1426 | 0.6771 |
| 0.3948 | 0.67 | 1200 | 1.1533 | 0.6701 |
| 0.3258 | 0.72 | 1300 | 1.1405 | 0.6743 |
| 0.3816 | 0.78 | 1400 | 1.1101 | 0.6838 |
| 0.308 | 0.84 | 1500 | 1.1281 | 0.6871 |
| 0.4592 | 0.89 | 1600 | 1.0971 | 0.6938 |
| 0.3957 | 0.95 | 1700 | 1.0586 | 0.6952 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.13.3
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Dec 28, 2023
- Updated
- Dec 28, 2023