| --- |
| 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: 0.59375 |
| --- |
| |
| <!-- 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: 1.1554 |
| - 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 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 20 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 1.2477 | 1.0 | 10 | 1.3618 | 0.5625 | |
| | 1.2002 | 2.0 | 20 | 1.3367 | 0.5625 | |
| | 1.111 | 3.0 | 30 | 1.3178 | 0.5312 | |
| | 1.0286 | 4.0 | 40 | 1.2215 | 0.5625 | |
| | 0.9376 | 5.0 | 50 | 1.2117 | 0.5437 | |
| | 0.8948 | 6.0 | 60 | 1.2304 | 0.5625 | |
| | 0.8234 | 7.0 | 70 | 1.1634 | 0.5563 | |
| | 0.8069 | 8.0 | 80 | 1.2422 | 0.5563 | |
| | 0.7146 | 9.0 | 90 | 1.2053 | 0.5563 | |
| | 0.709 | 10.0 | 100 | 1.1887 | 0.575 | |
| | 0.6404 | 11.0 | 110 | 1.2208 | 0.5563 | |
| | 0.6301 | 12.0 | 120 | 1.2319 | 0.5687 | |
| | 0.6107 | 13.0 | 130 | 1.1684 | 0.6 | |
| | 0.5825 | 14.0 | 140 | 1.1837 | 0.5813 | |
| | 0.5454 | 15.0 | 150 | 1.1818 | 0.5687 | |
| | 0.5517 | 16.0 | 160 | 1.1974 | 0.55 | |
| | 0.4989 | 17.0 | 170 | 1.1304 | 0.6 | |
| | 0.4875 | 18.0 | 180 | 1.2277 | 0.5375 | |
| | 0.4881 | 19.0 | 190 | 1.1363 | 0.5875 | |
| | 0.4951 | 20.0 | 200 | 1.1540 | 0.6062 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.33.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
| |
