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kazuma313
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emotion_classification

Image Classification
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vit
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End of training

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  1. README.md +28 -17
  2. model.safetensors +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: 0.29375
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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: 1.9514
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- - Accuracy: 0.2938
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  ## Model description
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  ### Training hyperparameters
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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: 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: 10
 
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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 | 2.0630 | 0.1625 |
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- | No log | 2.0 | 80 | 2.0519 | 0.1938 |
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- | No log | 3.0 | 120 | 2.0296 | 0.2625 |
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- | No log | 4.0 | 160 | 2.0237 | 0.2437 |
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- | No log | 5.0 | 200 | 1.9941 | 0.275 |
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- | No log | 6.0 | 240 | 1.9767 | 0.325 |
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- | No log | 7.0 | 280 | 1.9670 | 0.325 |
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- | No log | 8.0 | 320 | 1.9712 | 0.3063 |
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- | No log | 9.0 | 360 | 1.9588 | 0.35 |
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- | No log | 10.0 | 400 | 1.9514 | 0.2938 |
 
 
 
 
 
 
 
 
 
 
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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: 0.49375
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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: 1.3840
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+ - Accuracy: 0.4938
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.00012
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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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 20
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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 | 10 | 2.0302 | 0.2562 |
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+ | No log | 2.0 | 20 | 1.8255 | 0.4188 |
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+ | No log | 3.0 | 30 | 1.5799 | 0.3688 |
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+ | No log | 4.0 | 40 | 1.4107 | 0.5062 |
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+ | No log | 5.0 | 50 | 1.3364 | 0.5375 |
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+ | No log | 6.0 | 60 | 1.3316 | 0.5125 |
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+ | No log | 7.0 | 70 | 1.3021 | 0.5375 |
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+ | No log | 8.0 | 80 | 1.2880 | 0.5375 |
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+ | No log | 9.0 | 90 | 1.2682 | 0.5188 |
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+ | No log | 10.0 | 100 | 1.2936 | 0.5125 |
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+ | No log | 11.0 | 110 | 1.3376 | 0.5 |
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+ | No log | 12.0 | 120 | 1.2905 | 0.5563 |
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+ | No log | 13.0 | 130 | 1.2518 | 0.5062 |
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+ | No log | 14.0 | 140 | 1.2633 | 0.5437 |
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+ | No log | 15.0 | 150 | 1.4656 | 0.4313 |
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+ | No log | 16.0 | 160 | 1.2513 | 0.575 |
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+ | No log | 17.0 | 170 | 1.3498 | 0.4938 |
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+ | No log | 18.0 | 180 | 1.3155 | 0.5062 |
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+ | No log | 19.0 | 190 | 1.3673 | 0.5 |
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+ | No log | 20.0 | 200 | 1.3840 | 0.4938 |
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  ### Framework versions
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