| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: vit-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: 0.525 |
| --- |
| |
| <!-- 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. --> |
|
|
| # vit-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: 1.3506 |
| - Accuracy: 0.525 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 25 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 20 | 2.0656 | 0.1938 | |
| | No log | 2.0 | 40 | 2.0408 | 0.2625 | |
| | No log | 3.0 | 60 | 1.9845 | 0.275 | |
| | No log | 4.0 | 80 | 1.8774 | 0.35 | |
| | 1.9717 | 5.0 | 100 | 1.7409 | 0.45 | |
| | 1.9717 | 6.0 | 120 | 1.6349 | 0.4437 | |
| | 1.9717 | 7.0 | 140 | 1.5541 | 0.4437 | |
| | 1.9717 | 8.0 | 160 | 1.5007 | 0.5188 | |
| | 1.9717 | 9.0 | 180 | 1.4531 | 0.525 | |
| | 1.4968 | 10.0 | 200 | 1.4263 | 0.5312 | |
| | 1.4968 | 11.0 | 220 | 1.3975 | 0.5188 | |
| | 1.4968 | 12.0 | 240 | 1.3915 | 0.525 | |
| | 1.4968 | 13.0 | 260 | 1.3270 | 0.5375 | |
| | 1.4968 | 14.0 | 280 | 1.3360 | 0.575 | |
| | 1.2146 | 15.0 | 300 | 1.3185 | 0.5437 | |
| | 1.2146 | 16.0 | 320 | 1.3288 | 0.55 | |
| | 1.2146 | 17.0 | 340 | 1.3262 | 0.5563 | |
| | 1.2146 | 18.0 | 360 | 1.3142 | 0.55 | |
| | 1.2146 | 19.0 | 380 | 1.2982 | 0.5625 | |
| | 1.0644 | 20.0 | 400 | 1.2704 | 0.5625 | |
| | 1.0644 | 21.0 | 420 | 1.2862 | 0.55 | |
| | 1.0644 | 22.0 | 440 | 1.2941 | 0.55 | |
| | 1.0644 | 23.0 | 460 | 1.2876 | 0.5312 | |
| | 1.0644 | 24.0 | 480 | 1.3066 | 0.5625 | |
| | 1.0161 | 25.0 | 500 | 1.2734 | 0.55 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.48.3 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.0 |
| |
