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Kukuru0917
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emotion_classification

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
Kukuru0917 commited on
Commit
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End of training

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Files changed (2) hide show
  1. README.md +25 -25
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.55625
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 1.3006
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- - Accuracy: 0.5563
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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- - train_batch_size: 30
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- - eval_batch_size: 30
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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
@@ -64,26 +64,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 22 | 1.8368 | 0.425 |
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- | No log | 2.0 | 44 | 1.6260 | 0.375 |
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- | No log | 3.0 | 66 | 1.4368 | 0.5 |
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- | No log | 4.0 | 88 | 1.3790 | 0.5062 |
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- | No log | 5.0 | 110 | 1.3382 | 0.5125 |
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- | No log | 6.0 | 132 | 1.3136 | 0.4938 |
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- | No log | 7.0 | 154 | 1.2557 | 0.4938 |
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- | No log | 8.0 | 176 | 1.2959 | 0.5 |
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- | No log | 9.0 | 198 | 1.2810 | 0.5125 |
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- | No log | 10.0 | 220 | 1.2689 | 0.5563 |
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- | No log | 11.0 | 242 | 1.3548 | 0.4875 |
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- | No log | 12.0 | 264 | 1.2026 | 0.5563 |
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- | No log | 13.0 | 286 | 1.2096 | 0.575 |
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- | No log | 14.0 | 308 | 1.3175 | 0.525 |
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- | No log | 15.0 | 330 | 1.3121 | 0.5312 |
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- | No log | 16.0 | 352 | 1.4260 | 0.5312 |
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- | No log | 17.0 | 374 | 1.4547 | 0.5062 |
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- | No log | 18.0 | 396 | 1.3529 | 0.525 |
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- | No log | 19.0 | 418 | 1.2386 | 0.5938 |
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- | No log | 20.0 | 440 | 1.3504 | 0.5375 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.6375
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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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  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: 1.2745
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+ - Accuracy: 0.6375
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 20 | 1.7629 | 0.4375 |
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+ | No log | 2.0 | 40 | 1.5012 | 0.5 |
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+ | No log | 3.0 | 60 | 1.3757 | 0.5 |
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+ | No log | 4.0 | 80 | 1.2452 | 0.5625 |
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+ | No log | 5.0 | 100 | 1.2394 | 0.5625 |
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+ | No log | 6.0 | 120 | 1.2083 | 0.6125 |
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+ | No log | 7.0 | 140 | 1.2209 | 0.575 |
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+ | No log | 8.0 | 160 | 1.2755 | 0.5875 |
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+ | No log | 9.0 | 180 | 1.2794 | 0.5687 |
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+ | No log | 10.0 | 200 | 1.2639 | 0.6125 |
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+ | No log | 11.0 | 220 | 1.3129 | 0.6125 |
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+ | No log | 12.0 | 240 | 1.2277 | 0.6312 |
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+ | No log | 13.0 | 260 | 1.3620 | 0.5938 |
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+ | No log | 14.0 | 280 | 1.3023 | 0.6062 |
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+ | No log | 15.0 | 300 | 1.3334 | 0.6 |
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+ | No log | 16.0 | 320 | 1.4142 | 0.5813 |
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+ | No log | 17.0 | 340 | 1.2863 | 0.6125 |
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+ | No log | 18.0 | 360 | 1.4084 | 0.5875 |
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+ | No log | 19.0 | 380 | 1.4195 | 0.575 |
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+ | No log | 20.0 | 400 | 1.4164 | 0.5938 |
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  ### Framework versions
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