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ozair23
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mobilenet_v2_1.0_224-finetuned-plantdisease

Image Classification
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mobilenet_v2
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Eval Results (legacy)
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  1. README.md +16 -26
  2. model.safetensors +1 -1
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9781976744186046
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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
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0841
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- - Accuracy: 0.9782
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  ## Model description
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@@ -62,32 +62,22 @@ 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: 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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- | 1.7982 | 0.9983 | 145 | 1.9825 | 0.4036 |
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- | 0.6137 | 1.9966 | 290 | 1.1130 | 0.6415 |
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- | 0.4176 | 2.9948 | 435 | 0.4887 | 0.8469 |
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- | 0.3107 | 4.0 | 581 | 0.3414 | 0.8944 |
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- | 0.2255 | 4.9983 | 726 | 0.2732 | 0.9123 |
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- | 0.1833 | 5.9966 | 871 | 0.7462 | 0.7582 |
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- | 0.2062 | 6.9948 | 1016 | 0.3771 | 0.8803 |
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- | 0.1657 | 8.0 | 1162 | 0.4718 | 0.8542 |
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- | 0.1427 | 8.9983 | 1307 | 0.4902 | 0.8474 |
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- | 0.1598 | 9.9966 | 1452 | 0.2229 | 0.9273 |
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- | 0.1504 | 10.9948 | 1597 | 0.3021 | 0.8973 |
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- | 0.1456 | 12.0 | 1743 | 0.2422 | 0.9225 |
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- | 0.119 | 12.9983 | 1888 | 0.2836 | 0.9021 |
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- | 0.114 | 13.9966 | 2033 | 0.2038 | 0.9293 |
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- | 0.1378 | 14.9948 | 2178 | 0.2173 | 0.9239 |
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- | 0.1249 | 16.0 | 2324 | 0.2467 | 0.9186 |
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- | 0.1504 | 16.9983 | 2469 | 0.2322 | 0.9254 |
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- | 0.0972 | 17.9966 | 2614 | 0.0841 | 0.9782 |
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- | 0.1293 | 18.9948 | 2759 | 0.1512 | 0.9467 |
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- | 0.1072 | 19.9656 | 2900 | 0.1663 | 0.9448 |
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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: 0.9750797937638105
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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/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0750
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+ - Accuracy: 0.9751
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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: 10
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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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+ | 0.3974 | 0.9996 | 1145 | 0.3599 | 0.8979 |
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+ | 0.2155 | 2.0 | 2291 | 0.1525 | 0.9603 |
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+ | 0.2058 | 2.9996 | 3436 | 0.1492 | 0.9559 |
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+ | 0.1524 | 4.0 | 4582 | 0.1025 | 0.9694 |
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+ | 0.1274 | 4.9996 | 5727 | 0.0928 | 0.9706 |
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+ | 0.1141 | 6.0 | 6873 | 0.0874 | 0.9723 |
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+ | 0.1275 | 6.9996 | 8018 | 0.1226 | 0.9620 |
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+ | 0.1323 | 8.0 | 9164 | 0.0702 | 0.9777 |
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+ | 0.1212 | 8.9996 | 10309 | 0.1257 | 0.9607 |
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+ | 0.0981 | 9.9956 | 11450 | 0.0750 | 0.9751 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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