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jayanthspratap
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vit-base-patch16-224

Image Classification
Transformers
TensorBoard
Safetensors
swinv2
Generated from Trainer
Eval Results
Inference Endpoints
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jayanthspratap commited on
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  1. README.md +15 -15
  2. model.safetensors +1 -1
  3. runs/Aug10_00-00-02_EMIMDGXA100GPU1/events.out.tfevents.1723262404.EMIMDGXA100GPU1.4102242.0 +2 -2
README.md CHANGED
@@ -20,7 +20,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.6984126984126984
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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
@@ -30,8 +30,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6463
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- - Accuracy: 0.6984
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  ## Model description
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@@ -65,21 +65,21 @@ 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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- | 0.6893 | 1.0 | 35 | 0.7319 | 0.4127 |
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- | 0.702 | 2.0 | 70 | 0.6863 | 0.5238 |
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- | 0.6644 | 3.0 | 105 | 0.6796 | 0.5873 |
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- | 0.645 | 4.0 | 140 | 0.6722 | 0.5714 |
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- | 0.6455 | 5.0 | 175 | 0.6545 | 0.6508 |
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- | 0.6456 | 6.0 | 210 | 0.6536 | 0.6508 |
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- | 0.6745 | 7.0 | 245 | 0.6463 | 0.6984 |
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- | 0.6369 | 8.0 | 280 | 0.6525 | 0.6667 |
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- | 0.6012 | 9.0 | 315 | 0.6486 | 0.6984 |
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- | 0.6219 | 10.0 | 350 | 0.6466 | 0.6984 |
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  ### Framework versions
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- - Transformers 4.43.3
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- - Pytorch 2.4.0+cu118
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  - Datasets 2.20.0
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  - Tokenizers 0.19.1
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7333333333333333
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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 was trained from scratch on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5730
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+ - Accuracy: 0.7333
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 8 | 0.5546 | 0.8 |
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+ | 0.5945 | 2.0 | 16 | 0.5409 | 0.8 |
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+ | 0.5832 | 3.0 | 24 | 0.5467 | 0.8 |
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+ | 0.5338 | 4.0 | 32 | 0.5518 | 0.8 |
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+ | 0.5513 | 5.0 | 40 | 0.5602 | 0.8 |
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+ | 0.5513 | 6.0 | 48 | 0.5607 | 0.7333 |
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+ | 0.5417 | 7.0 | 56 | 0.5707 | 0.7333 |
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+ | 0.5343 | 8.0 | 64 | 0.5748 | 0.7333 |
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+ | 0.5379 | 9.0 | 72 | 0.5736 | 0.7333 |
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+ | 0.5137 | 10.0 | 80 | 0.5730 | 0.7333 |
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  ### Framework versions
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+ - Transformers 4.42.3
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+ - Pytorch 2.3.1+cu118
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  - Datasets 2.20.0
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  - Tokenizers 0.19.1
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