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Image Classification
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PyTorch
vit
Generated from Trainer
Eval Results
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End of training

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  1. README.md +67 -38
  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: 0.5875
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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: 1.2119
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- - Accuracy: 0.5875
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  ## Model description
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@@ -52,7 +52,7 @@ More information needed
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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
@@ -60,45 +60,74 @@ The following hyperparameters were used during training:
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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: reduce_lr_on_plateau
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- - num_epochs: 41
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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 | 2.0638 | 0.1562 |
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- | No log | 2.0 | 5 | 2.0353 | 0.2 |
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- | No log | 2.8 | 7 | 1.9965 | 0.2687 |
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- | 1.9968 | 4.0 | 10 | 1.9289 | 0.3937 |
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- | 1.9968 | 4.8 | 12 | 1.8942 | 0.3125 |
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- | 1.9968 | 6.0 | 15 | 1.8054 | 0.4562 |
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- | 1.9968 | 6.8 | 17 | 1.7626 | 0.4313 |
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- | 1.7555 | 8.0 | 20 | 1.7078 | 0.4562 |
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- | 1.7555 | 8.8 | 22 | 1.6608 | 0.45 |
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- | 1.7555 | 10.0 | 25 | 1.6121 | 0.425 |
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- | 1.7555 | 10.8 | 27 | 1.5759 | 0.4813 |
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- | 1.5214 | 12.0 | 30 | 1.5340 | 0.4562 |
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- | 1.5214 | 12.8 | 32 | 1.5006 | 0.5062 |
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- | 1.5214 | 14.0 | 35 | 1.4956 | 0.4313 |
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- | 1.5214 | 14.8 | 37 | 1.4418 | 0.5125 |
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- | 1.3342 | 16.0 | 40 | 1.4236 | 0.525 |
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- | 1.3342 | 16.8 | 42 | 1.3784 | 0.55 |
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- | 1.3342 | 18.0 | 45 | 1.4367 | 0.4938 |
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- | 1.3342 | 18.8 | 47 | 1.3665 | 0.525 |
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- | 1.1553 | 20.0 | 50 | 1.3867 | 0.4813 |
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- | 1.1553 | 20.8 | 52 | 1.3536 | 0.5312 |
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- | 1.1553 | 22.0 | 55 | 1.3391 | 0.5125 |
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- | 1.1553 | 22.8 | 57 | 1.2930 | 0.5563 |
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- | 0.9972 | 24.0 | 60 | 1.2894 | 0.5375 |
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- | 0.9972 | 24.8 | 62 | 1.2802 | 0.5625 |
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- | 0.9972 | 26.0 | 65 | 1.2671 | 0.5687 |
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- | 0.9972 | 26.8 | 67 | 1.2491 | 0.5625 |
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- | 0.838 | 28.0 | 70 | 1.2907 | 0.5437 |
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- | 0.838 | 28.8 | 72 | 1.2806 | 0.5563 |
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- | 0.838 | 30.0 | 75 | 1.2228 | 0.5687 |
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- | 0.838 | 30.8 | 77 | 1.2485 | 0.575 |
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- | 0.7226 | 32.0 | 80 | 1.2777 | 0.5437 |
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- | 0.7226 | 32.8 | 82 | 1.2106 | 0.6 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.6
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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: 1.2976
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+ - Accuracy: 0.6
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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: 7e-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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  - 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: reduce_lr_on_plateau
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+ - num_epochs: 77
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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 | 2.0706 | 0.15 |
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+ | No log | 2.0 | 5 | 2.0309 | 0.2313 |
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+ | No log | 2.8 | 7 | 1.9846 | 0.2562 |
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+ | 1.9868 | 4.0 | 10 | 1.8915 | 0.4062 |
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+ | 1.9868 | 4.8 | 12 | 1.8529 | 0.3125 |
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+ | 1.9868 | 6.0 | 15 | 1.7422 | 0.4125 |
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+ | 1.9868 | 6.8 | 17 | 1.6761 | 0.4313 |
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+ | 1.6815 | 8.0 | 20 | 1.6310 | 0.4562 |
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+ | 1.6815 | 8.8 | 22 | 1.5900 | 0.45 |
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+ | 1.6815 | 10.0 | 25 | 1.5402 | 0.4313 |
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+ | 1.6815 | 10.8 | 27 | 1.5018 | 0.5 |
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+ | 1.4233 | 12.0 | 30 | 1.4620 | 0.4875 |
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+ | 1.4233 | 12.8 | 32 | 1.4286 | 0.5062 |
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+ | 1.4233 | 14.0 | 35 | 1.4045 | 0.5125 |
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+ | 1.4233 | 14.8 | 37 | 1.3860 | 0.5312 |
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+ | 1.2127 | 16.0 | 40 | 1.3571 | 0.5 |
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+ | 1.2127 | 16.8 | 42 | 1.3293 | 0.5375 |
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+ | 1.2127 | 18.0 | 45 | 1.3742 | 0.4813 |
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+ | 1.2127 | 18.8 | 47 | 1.3151 | 0.5437 |
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+ | 1.0075 | 20.0 | 50 | 1.3053 | 0.5312 |
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+ | 1.0075 | 20.8 | 52 | 1.3266 | 0.5375 |
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+ | 1.0075 | 22.0 | 55 | 1.2964 | 0.5312 |
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+ | 1.0075 | 22.8 | 57 | 1.2278 | 0.5875 |
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+ | 0.8232 | 24.0 | 60 | 1.2501 | 0.5563 |
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+ | 0.8232 | 24.8 | 62 | 1.2330 | 0.575 |
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+ | 0.8232 | 26.0 | 65 | 1.2198 | 0.5625 |
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+ | 0.8232 | 26.8 | 67 | 1.2071 | 0.5875 |
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+ | 0.6738 | 28.0 | 70 | 1.2643 | 0.5875 |
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+ | 0.6738 | 28.8 | 72 | 1.2594 | 0.5563 |
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+ | 0.6738 | 30.0 | 75 | 1.2263 | 0.5312 |
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+ | 0.6738 | 30.8 | 77 | 1.3218 | 0.5188 |
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+ | 0.5715 | 32.0 | 80 | 1.2593 | 0.5312 |
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+ | 0.5715 | 32.8 | 82 | 1.2214 | 0.5625 |
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+ | 0.5715 | 34.0 | 85 | 1.3060 | 0.55 |
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+ | 0.5715 | 34.8 | 87 | 1.2727 | 0.5563 |
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+ | 0.4523 | 36.0 | 90 | 1.2749 | 0.5375 |
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+ | 0.4523 | 36.8 | 92 | 1.3570 | 0.5437 |
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+ | 0.4523 | 38.0 | 95 | 1.2815 | 0.5687 |
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+ | 0.4523 | 38.8 | 97 | 1.2233 | 0.6062 |
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+ | 0.3971 | 40.0 | 100 | 1.2097 | 0.6 |
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+ | 0.3971 | 40.8 | 102 | 1.2881 | 0.5813 |
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+ | 0.3971 | 42.0 | 105 | 1.2400 | 0.575 |
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+ | 0.3971 | 42.8 | 107 | 1.3140 | 0.5375 |
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+ | 0.3616 | 44.0 | 110 | 1.1525 | 0.6125 |
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+ | 0.3616 | 44.8 | 112 | 1.2725 | 0.5938 |
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+ | 0.3616 | 46.0 | 115 | 1.2634 | 0.5813 |
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+ | 0.3616 | 46.8 | 117 | 1.2299 | 0.6 |
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+ | 0.338 | 48.0 | 120 | 1.3408 | 0.5375 |
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+ | 0.338 | 48.8 | 122 | 1.1931 | 0.5938 |
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+ | 0.338 | 50.0 | 125 | 1.2806 | 0.5938 |
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+ | 0.338 | 50.8 | 127 | 1.2410 | 0.575 |
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+ | 0.3445 | 52.0 | 130 | 1.2901 | 0.5813 |
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+ | 0.3445 | 52.8 | 132 | 1.2504 | 0.6062 |
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+ | 0.3445 | 54.0 | 135 | 1.1614 | 0.5875 |
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+ | 0.3445 | 54.8 | 137 | 1.2247 | 0.6062 |
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+ | 0.3299 | 56.0 | 140 | 1.2591 | 0.5625 |
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+ | 0.3299 | 56.8 | 142 | 1.2629 | 0.5687 |
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+ | 0.3299 | 58.0 | 145 | 1.2369 | 0.5938 |
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+ | 0.3299 | 58.8 | 147 | 1.2771 | 0.575 |
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+ | 0.3292 | 60.0 | 150 | 1.3284 | 0.5875 |
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+ | 0.3292 | 60.8 | 152 | 1.2550 | 0.5625 |
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+ | 0.3292 | 61.6 | 154 | 1.3047 | 0.55 |
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  ### Framework versions
pytorch_model.bin CHANGED
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