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habibi26
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document-spoof-clip

Image Classification
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Safetensors
clip
Generated from Trainer
Eval Results
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  1. README.md +21 -17
  2. model.safetensors +1 -1
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9857142857142858
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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
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0284
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- - Accuracy: 0.9857
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  ## Model description
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@@ -60,25 +60,29 @@ The following hyperparameters were used during training:
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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: 15
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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 | 0.8421 | 4 | 0.5341 | 0.8286 |
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- | No log | 1.8947 | 9 | 0.2827 | 0.8857 |
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- | 0.6045 | 2.9474 | 14 | 0.4044 | 0.7857 |
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- | 0.6045 | 4.0 | 19 | 0.2278 | 0.9143 |
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- | 0.7684 | 4.8421 | 23 | 0.1033 | 0.9571 |
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- | 0.7684 | 5.8947 | 28 | 0.1466 | 0.9714 |
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- | 0.2323 | 6.9474 | 33 | 0.2253 | 0.9143 |
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- | 0.2323 | 8.0 | 38 | 0.1232 | 0.9714 |
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- | 0.0933 | 8.8421 | 42 | 0.0582 | 0.9714 |
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- | 0.0933 | 9.8947 | 47 | 0.0609 | 0.9714 |
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- | 0.067 | 10.9474 | 52 | 0.0453 | 0.9714 |
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- | 0.067 | 12.0 | 57 | 0.0422 | 0.9857 |
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- | 0.0835 | 12.6316 | 60 | 0.0284 | 0.9857 |
 
 
 
 
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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: 0.9428571428571428
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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 [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2587
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+ - Accuracy: 0.9429
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  ## Model description
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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 | 0.8421 | 4 | 0.2112 | 0.9571 |
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+ | No log | 1.8947 | 9 | 0.1227 | 0.9857 |
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+ | 0.295 | 2.9474 | 14 | 0.1203 | 0.9571 |
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+ | 0.295 | 4.0 | 19 | 0.0635 | 0.9714 |
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+ | 0.0962 | 4.8421 | 23 | 0.2939 | 0.9429 |
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+ | 0.0962 | 5.8947 | 28 | 0.2483 | 0.9286 |
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+ | 0.163 | 6.9474 | 33 | 0.0712 | 0.9857 |
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+ | 0.163 | 8.0 | 38 | 0.0474 | 0.9714 |
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+ | 0.0646 | 8.8421 | 42 | 0.2012 | 0.9429 |
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+ | 0.0646 | 9.8947 | 47 | 0.3587 | 0.9 |
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+ | 0.1048 | 10.9474 | 52 | 0.0427 | 0.9857 |
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+ | 0.1048 | 12.0 | 57 | 0.0149 | 0.9857 |
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+ | 0.0519 | 12.8421 | 61 | 0.1616 | 0.9571 |
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+ | 0.0519 | 13.8947 | 66 | 0.2286 | 0.9571 |
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+ | 0.0151 | 14.9474 | 71 | 0.1369 | 0.9571 |
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+ | 0.0151 | 16.0 | 76 | 0.2154 | 0.9571 |
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+ | 0.0455 | 16.8421 | 80 | 0.2587 | 0.9429 |
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  ### Framework versions
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