| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: google/vit-large-patch16-224-in21k |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: image_emotion_classification_project_4 |
| | 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: 0.51875 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # image_emotion_classification_project_4 |
| |
|
| | This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the imagefolder dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.9052 |
| | - 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: 1e-05 |
| | - train_batch_size: 1 |
| | - eval_batch_size: 1 |
| | - seed: 42 |
| | - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: reduce_lr_on_plateau |
| | - lr_scheduler_warmup_steps: 50 |
| | - num_epochs: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 1.6977 | 1.0 | 640 | 1.5713 | 0.325 | |
| | | 1.7006 | 2.0 | 1280 | 1.4543 | 0.4562 | |
| | | 1.6725 | 3.0 | 1920 | 1.6124 | 0.4625 | |
| | | 1.2312 | 4.0 | 2560 | 1.6711 | 0.5 | |
| | | 0.6097 | 5.0 | 3200 | 1.8838 | 0.5312 | |
| | | 1.264 | 6.0 | 3840 | 2.0933 | 0.4875 | |
| | | 2.4064 | 7.0 | 4480 | 2.0628 | 0.5188 | |
| | | 2.0741 | 8.0 | 5120 | 2.6505 | 0.4625 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.2 |
| | - Pytorch 2.5.0+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| |
|
