Downloads · 30 days
3
7% of all-time downloads
emotional_classification
Ghiffari4869/emotional_classification
emotional_classification is a image classification model from Ghiffari4869. 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
42
Public
Parameters
85.8M
687 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors343 MB · 100%
At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Feb 11, 2024
- Updated
- Feb 11, 2024
- SHA
- 9140697b
Base models
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. -->
emotional_classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.1401
- Accuracy: 0.5938
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 40 | 1.7535 | 0.3375 |
| No log | 2.0 | 80 | 1.5659 | 0.3875 |
| No log | 3.0 | 120 | 1.4480 | 0.4562 |
| No log | 4.0 | 160 | 1.3839 | 0.4938 |
| No log | 5.0 | 200 | 1.3246 | 0.5125 |
| No log | 6.0 | 240 | 1.3297 | 0.4875 |
| No log | 7.0 | 280 | 1.2665 | 0.5312 |
| No log | 8.0 | 320 | 1.2979 | 0.5625 |
| No log | 9.0 | 360 | 1.1959 | 0.5687 |
| No log | 10.0 | 400 | 1.2104 | 0.55 |
| No log | 11.0 | 440 | 1.2401 | 0.5687 |
| No log | 12.0 | 480 | 1.1960 | 0.5437 |
| 1.0885 | 13.0 | 520 | 1.1571 | 0.6188 |
| 1.0885 | 14.0 | 560 | 1.2241 | 0.575 |
| 1.0885 | 15.0 | 600 | 1.2355 | 0.5625 |
| 1.0885 | 16.0 | 640 | 1.1830 | 0.6 |
| 1.0885 | 17.0 | 680 | 1.2906 | 0.5625 |
| 1.0885 | 18.0 | 720 | 1.2705 | 0.525 |
| 1.0885 | 19.0 | 760 | 1.2643 | 0.5563 |
| 1.0885 | 20.0 | 800 | 1.1538 | 0.5813 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Feb 11, 2024
- Updated
- Feb 11, 2024