Downloads · 30 days
4
19% of all-time downloads
emotion_recog
Andhikuys/emotion_recog
emotion_recog is a image classification model from Andhikuys. 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
21
Public
Parameters
85.8M
343 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
- Jun 4, 2024
- Updated
- Jun 4, 2024
- SHA
- 01ad1cb2
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. -->
emotion_recog
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: 1.2377
- Accuracy: 0.5375
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: 64
- eval_batch_size: 64
- 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 | 10 | 1.6772 | 0.4062 |
| No log | 2.0 | 20 | 1.5802 | 0.4437 |
| No log | 3.0 | 30 | 1.4877 | 0.4875 |
| No log | 4.0 | 40 | 1.4649 | 0.475 |
| No log | 5.0 | 50 | 1.4092 | 0.5 |
| No log | 6.0 | 60 | 1.3454 | 0.5188 |
| No log | 7.0 | 70 | 1.3469 | 0.5312 |
| No log | 8.0 | 80 | 1.3010 | 0.5375 |
| No log | 9.0 | 90 | 1.2688 | 0.5563 |
| No log | 10.0 | 100 | 1.2854 | 0.5563 |
| No log | 11.0 | 110 | 1.2516 | 0.5437 |
| No log | 12.0 | 120 | 1.2819 | 0.5312 |
| No log | 13.0 | 130 | 1.2228 | 0.5875 |
| No log | 14.0 | 140 | 1.2250 | 0.5813 |
| No log | 15.0 | 150 | 1.2177 | 0.5563 |
| No log | 16.0 | 160 | 1.2172 | 0.55 |
| No log | 17.0 | 170 | 1.2198 | 0.6 |
| No log | 18.0 | 180 | 1.2341 | 0.5563 |
| No log | 19.0 | 190 | 1.2206 | 0.6 |
| No log | 20.0 | 200 | 1.1635 | 0.5813 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jun 4, 2024
- Updated
- Jun 4, 2024