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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: emotion_face_image_classification_v2 |
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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: 0.48125 |
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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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# emotion_face_image_classification_v2 |
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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: 1.5157 |
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- Accuracy: 0.4813 |
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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: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_ratio: 0.1 |
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- lr_scheduler_warmup_steps: 150 |
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- num_epochs: 50 |
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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 | 0.8 | 2 | 2.0924 | 0.15 | |
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| No log | 2.0 | 5 | 2.1024 | 0.0938 | |
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| No log | 2.8 | 7 | 2.0935 | 0.1375 | |
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| No log | 4.0 | 10 | 2.0893 | 0.15 | |
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| No log | 4.8 | 12 | 2.0900 | 0.15 | |
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| No log | 6.0 | 15 | 2.0987 | 0.0813 | |
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| No log | 6.8 | 17 | 2.0901 | 0.1 | |
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| No log | 8.0 | 20 | 2.0872 | 0.15 | |
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| No log | 8.8 | 22 | 2.0831 | 0.1375 | |
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| No log | 10.0 | 25 | 2.0750 | 0.1437 | |
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| No log | 10.8 | 27 | 2.0744 | 0.175 | |
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| No log | 12.0 | 30 | 2.0778 | 0.1437 | |
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| No log | 12.8 | 32 | 2.0729 | 0.1812 | |
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| No log | 14.0 | 35 | 2.0676 | 0.1625 | |
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| No log | 14.8 | 37 | 2.0694 | 0.1688 | |
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| No log | 16.0 | 40 | 2.0562 | 0.1625 | |
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| No log | 16.8 | 42 | 2.0498 | 0.1938 | |
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| No log | 18.0 | 45 | 2.0393 | 0.2188 | |
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| No log | 18.8 | 47 | 2.0458 | 0.2062 | |
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| No log | 20.0 | 50 | 2.0289 | 0.2125 | |
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| No log | 20.8 | 52 | 2.0226 | 0.2437 | |
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| No log | 22.0 | 55 | 1.9997 | 0.2625 | |
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| No log | 22.8 | 57 | 1.9855 | 0.3187 | |
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| No log | 24.0 | 60 | 1.9571 | 0.3187 | |
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| No log | 24.8 | 62 | 1.9473 | 0.3375 | |
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| No log | 26.0 | 65 | 1.9080 | 0.3187 | |
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| No log | 26.8 | 67 | 1.8894 | 0.35 | |
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| No log | 28.0 | 70 | 1.8407 | 0.375 | |
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| No log | 28.8 | 72 | 1.8083 | 0.3438 | |
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| No log | 30.0 | 75 | 1.7652 | 0.3563 | |
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| No log | 30.8 | 77 | 1.7281 | 0.3563 | |
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| No log | 32.0 | 80 | 1.6729 | 0.4062 | |
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| No log | 32.8 | 82 | 1.6527 | 0.3937 | |
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| No log | 34.0 | 85 | 1.6044 | 0.4562 | |
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| No log | 34.8 | 87 | 1.5899 | 0.4313 | |
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| No log | 36.0 | 90 | 1.5488 | 0.4313 | |
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| No log | 36.8 | 92 | 1.5340 | 0.45 | |
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| No log | 38.0 | 95 | 1.5227 | 0.4875 | |
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| No log | 38.8 | 97 | 1.4846 | 0.4875 | |
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| No log | 40.0 | 100 | 1.4579 | 0.4688 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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