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cat_dog_classifier_with_small_datasest

Image Classification
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resnet
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End of training

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  1. README.md +23 -23
  2. model.safetensors +1 -1
  3. training_args.bin +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: 0.8571428571428571
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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 [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5540
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- - Accuracy: 0.8571
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  ## Model description
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@@ -65,26 +65,26 @@ 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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- | No log | 1.0 | 140 | 0.5149 | 0.8143 |
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- | No log | 2.0 | 280 | 0.2519 | 0.9214 |
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- | No log | 3.0 | 420 | 0.3596 | 0.85 |
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- | 0.3145 | 4.0 | 560 | 0.2661 | 0.9214 |
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- | 0.3145 | 5.0 | 700 | 0.2600 | 0.8929 |
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- | 0.3145 | 6.0 | 840 | 0.1840 | 0.9286 |
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- | 0.3145 | 7.0 | 980 | 0.3145 | 0.9071 |
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- | 0.27 | 8.0 | 1120 | 0.2121 | 0.9214 |
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- | 0.27 | 9.0 | 1260 | 0.3926 | 0.8571 |
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- | 0.27 | 10.0 | 1400 | 0.3488 | 0.8786 |
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- | 0.2426 | 11.0 | 1540 | 0.2437 | 0.9071 |
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- | 0.2426 | 12.0 | 1680 | 0.2497 | 0.9 |
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- | 0.2426 | 13.0 | 1820 | 0.1663 | 0.9214 |
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- | 0.2426 | 14.0 | 1960 | 0.2132 | 0.9357 |
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- | 0.2556 | 15.0 | 2100 | 0.3464 | 0.8714 |
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- | 0.2556 | 16.0 | 2240 | 0.3063 | 0.9071 |
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- | 0.2556 | 17.0 | 2380 | 0.2992 | 0.9071 |
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- | 0.261 | 18.0 | 2520 | 0.3765 | 0.8857 |
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- | 0.261 | 19.0 | 2660 | 0.1396 | 0.9286 |
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- | 0.261 | 20.0 | 2800 | 0.5540 | 0.8571 |
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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: 0.8
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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 [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4506
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+ - Accuracy: 0.8
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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 | 140 | 0.6771 | 0.6786 |
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+ | No log | 2.0 | 280 | 0.6420 | 0.7429 |
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+ | No log | 3.0 | 420 | 0.5982 | 0.7286 |
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+ | 0.6043 | 4.0 | 560 | 0.4834 | 0.7929 |
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+ | 0.6043 | 5.0 | 700 | 0.4565 | 0.8071 |
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+ | 0.6043 | 6.0 | 840 | 0.3878 | 0.7857 |
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+ | 0.6043 | 7.0 | 980 | 0.4147 | 0.8286 |
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+ | 0.4152 | 8.0 | 1120 | 0.3455 | 0.85 |
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+ | 0.4152 | 9.0 | 1260 | 0.3802 | 0.8786 |
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+ | 0.4152 | 10.0 | 1400 | 0.3318 | 0.8857 |
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+ | 0.3497 | 11.0 | 1540 | 0.3170 | 0.85 |
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+ | 0.3497 | 12.0 | 1680 | 0.4438 | 0.8286 |
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+ | 0.3497 | 13.0 | 1820 | 0.3154 | 0.8857 |
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+ | 0.3497 | 14.0 | 1960 | 0.3921 | 0.8571 |
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+ | 0.3585 | 15.0 | 2100 | 0.2998 | 0.8929 |
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+ | 0.3585 | 16.0 | 2240 | 0.3220 | 0.8571 |
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+ | 0.3585 | 17.0 | 2380 | 0.2554 | 0.9286 |
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+ | 0.3466 | 18.0 | 2520 | 0.5321 | 0.85 |
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+ | 0.3466 | 19.0 | 2660 | 0.4611 | 0.8286 |
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+ | 0.3466 | 20.0 | 2800 | 0.4506 | 0.8 |
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  ### Framework versions
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