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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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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: visual_emotion_classification_vit_base_finetunned |
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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: 0.5125 |
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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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# visual_emotion_classification_vit_base_finetunned |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3576 |
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- Accuracy: 0.5125 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2.5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 40 | 1.9700 | 0.2625 | |
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| 2.0074 | 2.0 | 80 | 1.7194 | 0.3688 | |
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| 1.726 | 3.0 | 120 | 1.5775 | 0.3875 | |
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| 1.5202 | 4.0 | 160 | 1.4900 | 0.4875 | |
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| 1.3857 | 5.0 | 200 | 1.4261 | 0.4938 | |
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| 1.3857 | 6.0 | 240 | 1.4090 | 0.5 | |
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| 1.2831 | 7.0 | 280 | 1.3510 | 0.475 | |
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| 1.2007 | 8.0 | 320 | 1.3788 | 0.475 | |
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| 1.1256 | 9.0 | 360 | 1.3183 | 0.5 | |
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| 1.0345 | 10.0 | 400 | 1.2937 | 0.4813 | |
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| 1.0345 | 11.0 | 440 | 1.2384 | 0.5437 | |
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| 0.9438 | 12.0 | 480 | 1.2100 | 0.525 | |
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| 0.872 | 13.0 | 520 | 1.2450 | 0.525 | |
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| 0.8193 | 14.0 | 560 | 1.2264 | 0.5312 | |
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| 0.763 | 15.0 | 600 | 1.2296 | 0.5125 | |
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| 0.763 | 16.0 | 640 | 1.2539 | 0.5188 | |
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| 0.7166 | 17.0 | 680 | 1.2253 | 0.5563 | |
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| 0.6328 | 18.0 | 720 | 1.2723 | 0.5312 | |
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| 0.5917 | 19.0 | 760 | 1.2870 | 0.4875 | |
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| 0.5841 | 20.0 | 800 | 1.3011 | 0.5375 | |
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| 0.5841 | 21.0 | 840 | 1.2071 | 0.575 | |
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| 0.559 | 22.0 | 880 | 1.2555 | 0.575 | |
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| 0.5109 | 23.0 | 920 | 1.3140 | 0.5 | |
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| 0.5036 | 24.0 | 960 | 1.2593 | 0.5 | |
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| 0.4787 | 25.0 | 1000 | 1.2573 | 0.5813 | |
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| 0.4787 | 26.0 | 1040 | 1.2163 | 0.55 | |
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| 0.4583 | 27.0 | 1080 | 1.2349 | 0.5563 | |
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| 0.4766 | 28.0 | 1120 | 1.3349 | 0.5188 | |
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| 0.4709 | 29.0 | 1160 | 1.3284 | 0.5312 | |
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| 0.4442 | 30.0 | 1200 | 1.2684 | 0.5625 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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