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emotion_classification_2
raffel-22/emotion_classification_2
emotion_classification_2 is a image classification model from raffel-22. 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. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Sep 16, 2023
- Updated
- Sep 16, 2023
- SHA
- 77b6c302
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_classification_2
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: 1.3274
- Accuracy: 0.5188
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: 4e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 20 | 1.9337 | 0.3563 |
| No log | 2.0 | 40 | 1.7116 | 0.3375 |
| No log | 3.0 | 60 | 1.5755 | 0.4562 |
| No log | 4.0 | 80 | 1.4939 | 0.45 |
| No log | 5.0 | 100 | 1.4377 | 0.5062 |
| No log | 6.0 | 120 | 1.4363 | 0.4562 |
| No log | 7.0 | 140 | 1.3615 | 0.5125 |
| No log | 8.0 | 160 | 1.3021 | 0.5375 |
| No log | 9.0 | 180 | 1.3307 | 0.525 |
| No log | 10.0 | 200 | 1.3085 | 0.4938 |
| No log | 11.0 | 220 | 1.2798 | 0.5813 |
| No log | 12.0 | 240 | 1.2707 | 0.525 |
| No log | 13.0 | 260 | 1.2339 | 0.55 |
| No log | 14.0 | 280 | 1.3053 | 0.5437 |
| No log | 15.0 | 300 | 1.3038 | 0.4938 |
| No log | 16.0 | 320 | 1.3088 | 0.5375 |
| No log | 17.0 | 340 | 1.3336 | 0.5312 |
| No log | 18.0 | 360 | 1.3053 | 0.5 |
| No log | 19.0 | 380 | 1.2206 | 0.5687 |
| No log | 20.0 | 400 | 1.2598 | 0.5312 |
| No log | 21.0 | 420 | 1.3332 | 0.5125 |
| No log | 22.0 | 440 | 1.3388 | 0.5312 |
| No log | 23.0 | 460 | 1.3129 | 0.5563 |
| No log | 24.0 | 480 | 1.3632 | 0.5062 |
| 0.9153 | 25.0 | 500 | 1.4166 | 0.4688 |
| 0.9153 | 26.0 | 520 | 1.4094 | 0.5 |
| 0.9153 | 27.0 | 540 | 1.4294 | 0.475 |
| 0.9153 | 28.0 | 560 | 1.4937 | 0.475 |
| 0.9153 | 29.0 | 580 | 1.3897 | 0.4938 |
| 0.9153 | 30.0 | 600 | 1.4565 | 0.475 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Sep 16, 2023
- Updated
- Sep 16, 2023