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Image Classification
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clip
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  1. README.md +30 -30
  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: 0.945054945054945
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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: 0.2528
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- - Accuracy: 0.9451
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  ## Model description
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@@ -64,33 +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 | 0.9655 | 7 | 0.5985 | 0.6154 |
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- | No log | 1.9310 | 14 | 0.1681 | 0.9341 |
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- | 0.4711 | 2.8966 | 21 | 0.2271 | 0.9011 |
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- | 0.4711 | 4.0 | 29 | 0.8009 | 0.7473 |
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- | 0.3768 | 4.9655 | 36 | 0.1365 | 0.9560 |
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- | 0.3768 | 5.9310 | 43 | 0.1176 | 0.9780 |
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- | 0.069 | 6.8966 | 50 | 0.0880 | 0.9890 |
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- | 0.069 | 8.0 | 58 | 0.6839 | 0.9011 |
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- | 0.0212 | 8.9655 | 65 | 0.3376 | 0.9451 |
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- | 0.0212 | 9.9310 | 72 | 0.2240 | 0.9670 |
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- | 0.0201 | 10.8966 | 79 | 0.5612 | 0.9341 |
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- | 0.0201 | 12.0 | 87 | 0.2688 | 0.9560 |
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- | 0.0039 | 12.9655 | 94 | 0.1710 | 0.9780 |
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- | 0.0039 | 13.9310 | 101 | 0.3437 | 0.9560 |
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- | 0.0293 | 14.8966 | 108 | 0.2446 | 0.9670 |
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- | 0.0293 | 16.0 | 116 | 0.1507 | 0.9780 |
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- | 0.0009 | 16.9655 | 123 | 0.2032 | 0.9670 |
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- | 0.0009 | 17.9310 | 130 | 0.2481 | 0.9451 |
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- | 0.0 | 18.8966 | 137 | 0.2608 | 0.9451 |
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- | 0.0 | 20.0 | 145 | 0.2611 | 0.9451 |
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- | 0.0 | 20.9655 | 152 | 0.2579 | 0.9451 |
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- | 0.0 | 21.9310 | 159 | 0.2554 | 0.9451 |
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- | 0.0 | 22.8966 | 166 | 0.2536 | 0.9451 |
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- | 0.0 | 24.0 | 174 | 0.2528 | 0.9451 |
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- | 0.0 | 24.1379 | 175 | 0.2528 | 0.9451 |
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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: 0.8021978021978022
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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: 2.5306
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+ - Accuracy: 0.8022
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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 | 2 | 0.6707 | 0.6154 |
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+ | No log | 2.0 | 4 | 0.6923 | 0.6154 |
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+ | No log | 3.0 | 6 | 0.7209 | 0.7033 |
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+ | No log | 4.0 | 8 | 0.4789 | 0.8022 |
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+ | No log | 5.0 | 10 | 0.3554 | 0.9011 |
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+ | No log | 6.0 | 12 | 0.8338 | 0.8242 |
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+ | No log | 7.0 | 14 | 1.0734 | 0.7912 |
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+ | 0.2476 | 8.0 | 16 | 1.0161 | 0.8242 |
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+ | 0.2476 | 9.0 | 18 | 0.8967 | 0.8571 |
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+ | 0.2476 | 10.0 | 20 | 0.8477 | 0.8681 |
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+ | 0.2476 | 11.0 | 22 | 1.3332 | 0.8352 |
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+ | 0.2476 | 12.0 | 24 | 3.4776 | 0.7253 |
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+ | 0.2476 | 13.0 | 26 | 6.0098 | 0.6374 |
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+ | 0.2476 | 14.0 | 28 | 3.8650 | 0.7253 |
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+ | 0.0277 | 15.0 | 30 | 2.2410 | 0.8132 |
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+ | 0.0277 | 16.0 | 32 | 1.4585 | 0.8132 |
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+ | 0.0277 | 17.0 | 34 | 1.4790 | 0.8022 |
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+ | 0.0277 | 18.0 | 36 | 1.8427 | 0.8242 |
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+ | 0.0277 | 19.0 | 38 | 2.0874 | 0.8242 |
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+ | 0.0277 | 20.0 | 40 | 2.2456 | 0.8132 |
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+ | 0.0277 | 21.0 | 42 | 2.3663 | 0.8022 |
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+ | 0.0277 | 22.0 | 44 | 2.4484 | 0.8022 |
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+ | 0.0001 | 23.0 | 46 | 2.4974 | 0.8022 |
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+ | 0.0001 | 24.0 | 48 | 2.5221 | 0.8022 |
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+ | 0.0001 | 25.0 | 50 | 2.5306 | 0.8022 |
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  ### Framework versions
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