--- library_name: transformers license: apache-2.0 base_model: dima806/facial_emotions_image_detection tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: image_classification2 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: 0.66875 --- # image_classification2 This model is a fine-tuned version of [dima806/facial_emotions_image_detection](https://huggingface.co/dima806/facial_emotions_image_detection) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.9519 - Accuracy: 0.6687 ## 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: 2 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 8 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.8187 | 1.0 | 80 | 1.7527 | 0.4813 | | 1.52 | 2.0 | 160 | 1.3596 | 0.6312 | | 1.4072 | 3.0 | 240 | 1.2119 | 0.5875 | | 1.0868 | 4.0 | 320 | 1.0981 | 0.625 | | 0.9286 | 5.0 | 400 | 1.0133 | 0.6625 | | 0.9353 | 6.0 | 480 | 0.9711 | 0.625 | | 0.7437 | 7.0 | 560 | 0.9389 | 0.6562 | | 0.6774 | 8.0 | 640 | 0.9519 | 0.6687 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1