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habibi26
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ktp-not-ktp-clip

Image Classification
Transformers
TensorBoard
Safetensors
clip
Generated from Trainer
Eval Results
Inference Endpoints
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  1. README.md +30 -24
  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: 0.975
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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: 0.0267
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- - Accuracy: 0.975
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  ## Model description
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@@ -64,27 +64,33 @@ The following hyperparameters were used during training:
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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 | 0.7273 | 2 | 0.6196 | 0.75 |
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- | No log | 1.8182 | 5 | 0.2383 | 0.975 |
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- | No log | 2.9091 | 8 | 2.4068 | 0.5 |
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- | No log | 4.0 | 11 | 0.0973 | 0.95 |
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- | No log | 4.7273 | 13 | 0.0032 | 1.0 |
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- | 0.547 | 5.8182 | 16 | 0.1538 | 0.975 |
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- | 0.547 | 6.9091 | 19 | 0.0003 | 1.0 |
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- | 0.547 | 8.0 | 22 | 0.0028 | 1.0 |
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- | 0.547 | 8.7273 | 24 | 0.0092 | 1.0 |
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- | 0.547 | 9.8182 | 27 | 0.0318 | 0.975 |
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- | 0.0168 | 10.9091 | 30 | 0.0453 | 0.975 |
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- | 0.0168 | 12.0 | 33 | 0.0398 | 0.975 |
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- | 0.0168 | 12.7273 | 35 | 0.0366 | 0.975 |
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- | 0.0168 | 13.8182 | 38 | 0.0325 | 0.975 |
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- | 0.0168 | 14.9091 | 41 | 0.0298 | 0.975 |
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- | 0.0168 | 16.0 | 44 | 0.0280 | 0.975 |
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- | 0.0 | 16.7273 | 46 | 0.0273 | 0.975 |
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- | 0.0 | 17.8182 | 49 | 0.0268 | 0.975 |
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- | 0.0 | 18.1818 | 50 | 0.0267 | 0.975 |
 
 
 
 
 
 
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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: 0.989010989010989
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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: 0.1267
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+ - Accuracy: 0.9890
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  ## Model description
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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 | 7 | 0.5809 | 0.6374 |
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+ | No log | 2.0 | 14 | 1.3401 | 0.6703 |
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+ | 0.5558 | 3.0 | 21 | 0.6458 | 0.7692 |
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+ | 0.5558 | 4.0 | 28 | 0.3785 | 0.8681 |
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+ | 0.1701 | 5.0 | 35 | 0.3004 | 0.9451 |
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+ | 0.1701 | 6.0 | 42 | 0.2204 | 0.9560 |
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+ | 0.142 | 7.0 | 49 | 0.1483 | 0.9341 |
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+ | 0.142 | 8.0 | 56 | 0.1386 | 0.9670 |
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+ | 0.1002 | 9.0 | 63 | 0.7714 | 0.8681 |
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+ | 0.1002 | 10.0 | 70 | 0.2285 | 0.9341 |
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+ | 0.0956 | 11.0 | 77 | 0.1162 | 0.9780 |
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+ | 0.0956 | 12.0 | 84 | 0.1104 | 0.9780 |
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+ | 0.0004 | 13.0 | 91 | 0.1722 | 0.9780 |
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+ | 0.0004 | 14.0 | 98 | 0.2109 | 0.9780 |
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+ | 0.0209 | 15.0 | 105 | 0.3321 | 0.9560 |
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+ | 0.0209 | 16.0 | 112 | 0.0785 | 0.9780 |
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+ | 0.0209 | 17.0 | 119 | 0.1525 | 0.9670 |
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+ | 0.0014 | 18.0 | 126 | 0.1436 | 0.9670 |
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+ | 0.0014 | 19.0 | 133 | 0.2278 | 0.9670 |
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+ | 0.0002 | 20.0 | 140 | 0.3035 | 0.9560 |
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+ | 0.0002 | 21.0 | 147 | 0.1239 | 0.9780 |
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+ | 0.001 | 22.0 | 154 | 0.1211 | 0.9890 |
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+ | 0.001 | 23.0 | 161 | 0.1253 | 0.9890 |
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+ | 0.0 | 24.0 | 168 | 0.1265 | 0.9890 |
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+ | 0.0 | 25.0 | 175 | 0.1267 | 0.9890 |
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  ### Framework versions
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