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finetuned-FER2013

Image Classification
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Safetensors
beit
Generated from Trainer
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: finetuned-FER2013
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.6788575409265064
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # finetuned-FER2013
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+
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8812
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+ - Accuracy: 0.6789
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-06
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.5466 | 1.0 | 202 | 1.5022 | 0.4500 |
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+ | 1.3372 | 2.0 | 404 | 1.1727 | 0.5632 |
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+ | 1.2372 | 3.0 | 606 | 1.0636 | 0.6075 |
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+ | 1.2096 | 4.0 | 808 | 1.0200 | 0.6116 |
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+ | 1.145 | 5.0 | 1010 | 0.9769 | 0.6325 |
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+ | 1.1589 | 6.0 | 1212 | 0.9515 | 0.6405 |
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+ | 1.0752 | 7.0 | 1414 | 0.9395 | 0.6458 |
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+ | 1.0524 | 8.0 | 1616 | 0.9331 | 0.6458 |
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+ | 1.0829 | 9.0 | 1818 | 0.9173 | 0.6573 |
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+ | 1.0219 | 10.0 | 2020 | 0.9114 | 0.6597 |
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+ | 0.9986 | 11.0 | 2222 | 0.9034 | 0.6580 |
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+ | 1.013 | 12.0 | 2424 | 0.9004 | 0.6656 |
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+ | 1.0133 | 13.0 | 2626 | 0.8940 | 0.6628 |
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+ | 1.0064 | 14.0 | 2828 | 0.8916 | 0.6649 |
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+ | 0.9858 | 15.0 | 3030 | 0.8882 | 0.6733 |
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+ | 0.9863 | 16.0 | 3232 | 0.8850 | 0.6740 |
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+ | 1.0058 | 17.0 | 3434 | 0.8856 | 0.6747 |
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+ | 0.9637 | 18.0 | 3636 | 0.8852 | 0.6722 |
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+ | 0.9803 | 19.0 | 3838 | 0.8829 | 0.6754 |
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+ | 0.9356 | 20.0 | 4040 | 0.8812 | 0.6789 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0