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RickyIG
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emotion_face_image_classification

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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  2. pytorch_model.bin +1 -1
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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
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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: 0.55
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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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+ # emotion_face_image_classification
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+
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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: 1.2556
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+ - Accuracy: 0.55
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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-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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+ - 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: 50
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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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+ | No log | 1.0 | 10 | 2.0561 | 0.1437 |
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+ | No log | 2.0 | 20 | 1.9946 | 0.325 |
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+ | No log | 3.0 | 30 | 1.9059 | 0.3563 |
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+ | No log | 4.0 | 40 | 1.7640 | 0.3937 |
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+ | No log | 5.0 | 50 | 1.6329 | 0.3812 |
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+ | No log | 6.0 | 60 | 1.5935 | 0.375 |
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+ | No log | 7.0 | 70 | 1.5206 | 0.4313 |
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+ | No log | 8.0 | 80 | 1.4580 | 0.4813 |
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+ | No log | 9.0 | 90 | 1.4422 | 0.4938 |
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+ | No log | 10.0 | 100 | 1.4297 | 0.4437 |
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+ | No log | 11.0 | 110 | 1.4020 | 0.5062 |
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+ | No log | 12.0 | 120 | 1.3344 | 0.5125 |
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+ | No log | 13.0 | 130 | 1.3541 | 0.5125 |
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+ | No log | 14.0 | 140 | 1.2990 | 0.5125 |
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+ | No log | 15.0 | 150 | 1.2482 | 0.5687 |
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+ | No log | 16.0 | 160 | 1.2726 | 0.4875 |
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+ | No log | 17.0 | 170 | 1.2523 | 0.5375 |
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+ | No log | 18.0 | 180 | 1.2857 | 0.4813 |
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+ | No log | 19.0 | 190 | 1.2476 | 0.5375 |
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+ | No log | 20.0 | 200 | 1.2991 | 0.4625 |
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+ | No log | 21.0 | 210 | 1.3108 | 0.5062 |
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+ | No log | 22.0 | 220 | 1.3052 | 0.5 |
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+ | No log | 23.0 | 230 | 1.2606 | 0.4813 |
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+ | No log | 24.0 | 240 | 1.1568 | 0.5687 |
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+ | No log | 25.0 | 250 | 1.2242 | 0.5437 |
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+ | No log | 26.0 | 260 | 1.2031 | 0.5875 |
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+ | No log | 27.0 | 270 | 1.1649 | 0.5625 |
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+ | No log | 28.0 | 280 | 1.3134 | 0.4938 |
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+ | No log | 29.0 | 290 | 1.2542 | 0.5062 |
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+ | No log | 30.0 | 300 | 1.1542 | 0.5687 |
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+ | No log | 31.0 | 310 | 1.1619 | 0.5625 |
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+ | No log | 32.0 | 320 | 1.2700 | 0.5 |
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+ | No log | 33.0 | 330 | 1.1943 | 0.55 |
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+ | No log | 34.0 | 340 | 1.1441 | 0.575 |
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+ | No log | 35.0 | 350 | 1.2405 | 0.5687 |
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+ | No log | 36.0 | 360 | 1.2228 | 0.5375 |
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+ | No log | 37.0 | 370 | 1.1598 | 0.6 |
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+ | No log | 38.0 | 380 | 1.1894 | 0.5687 |
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+ | No log | 39.0 | 390 | 1.2493 | 0.5188 |
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+ | No log | 40.0 | 400 | 1.1716 | 0.5687 |
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+ | No log | 41.0 | 410 | 1.1558 | 0.5813 |
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+ | No log | 42.0 | 420 | 1.2529 | 0.5312 |
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+ | No log | 43.0 | 430 | 1.2515 | 0.5625 |
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+ | No log | 44.0 | 440 | 1.2576 | 0.5188 |
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+ | No log | 45.0 | 450 | 1.1793 | 0.5687 |
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+ | No log | 46.0 | 460 | 1.2252 | 0.5625 |
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+ | No log | 47.0 | 470 | 1.1876 | 0.575 |
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+ | No log | 48.0 | 480 | 1.2288 | 0.5375 |
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+ | No log | 49.0 | 490 | 1.2623 | 0.5125 |
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+ | 0.989 | 50.0 | 500 | 1.1603 | 0.5875 |
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+
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+
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+ ### Framework versions
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+
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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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