| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: emotion_classification |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.55 |
| --- |
| |
| <!-- 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 |
| |
| This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.3694 |
| - Accuracy: 0.55 |
| |
| ## 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: 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: 30 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 40 | 1.9385 | 0.35 | |
| | No log | 2.0 | 80 | 1.6433 | 0.3875 | |
| | No log | 3.0 | 120 | 1.4689 | 0.5375 | |
| | No log | 4.0 | 160 | 1.3533 | 0.55 | |
| | No log | 5.0 | 200 | 1.3162 | 0.5813 | |
| | No log | 6.0 | 240 | 1.3131 | 0.5437 | |
| | No log | 7.0 | 280 | 1.2160 | 0.6 | |
| | No log | 8.0 | 320 | 1.2660 | 0.5437 | |
| | No log | 9.0 | 360 | 1.2594 | 0.55 | |
| | No log | 10.0 | 400 | 1.1873 | 0.5687 | |
| | No log | 11.0 | 440 | 1.1169 | 0.5875 | |
| | No log | 12.0 | 480 | 1.2015 | 0.5687 | |
| | 1.125 | 13.0 | 520 | 1.2653 | 0.5375 | |
| | 1.125 | 14.0 | 560 | 1.2801 | 0.5563 | |
| | 1.125 | 15.0 | 600 | 1.2304 | 0.5563 | |
| | 1.125 | 16.0 | 640 | 1.2341 | 0.5437 | |
| | 1.125 | 17.0 | 680 | 1.2981 | 0.5312 | |
| | 1.125 | 18.0 | 720 | 1.3277 | 0.5687 | |
| | 1.125 | 19.0 | 760 | 1.2174 | 0.5875 | |
| | 1.125 | 20.0 | 800 | 1.1810 | 0.6 | |
| | 1.125 | 21.0 | 840 | 1.2280 | 0.5687 | |
| | 1.125 | 22.0 | 880 | 1.3576 | 0.525 | |
| | 1.125 | 23.0 | 920 | 1.3897 | 0.5375 | |
| | 1.125 | 24.0 | 960 | 1.3216 | 0.5625 | |
| | 0.3612 | 25.0 | 1000 | 1.3033 | 0.6062 | |
| | 0.3612 | 26.0 | 1040 | 1.3501 | 0.5625 | |
| | 0.3612 | 27.0 | 1080 | 1.2310 | 0.575 | |
| | 0.3612 | 28.0 | 1120 | 1.2495 | 0.6062 | |
| | 0.3612 | 29.0 | 1160 | 1.2974 | 0.5875 | |
| | 0.3612 | 30.0 | 1200 | 1.2985 | 0.5813 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.1 |
| |
