| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: Emotion_Classifier |
| 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: 0.6 |
| --- |
| |
| <!-- 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_Classifier |
| |
| 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: 1.1050 |
| - Accuracy: 0.6 |
| |
| ## 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: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 160 | 1.5776 | 0.4062 | |
| | No log | 2.0 | 320 | 1.3785 | 0.45 | |
| | No log | 3.0 | 480 | 1.2496 | 0.5437 | |
| | 1.5301 | 4.0 | 640 | 1.2040 | 0.5312 | |
| | 1.5301 | 5.0 | 800 | 1.1536 | 0.575 | |
| | 1.5301 | 6.0 | 960 | 1.1603 | 0.575 | |
| | 0.9484 | 7.0 | 1120 | 1.1435 | 0.575 | |
| | 0.9484 | 8.0 | 1280 | 1.1538 | 0.6125 | |
| | 0.9484 | 9.0 | 1440 | 1.1871 | 0.575 | |
| | 0.5674 | 10.0 | 1600 | 1.1620 | 0.6125 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.41.1 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.19.2 |
| - Tokenizers 0.19.1 |
| |
