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resnet-18-finetuned-fraud

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  1. README.md +24 -22
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,10 +1,12 @@
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  ---
 
 
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  tags:
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  - generated_from_trainer
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  datasets:
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  - imagefolder
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  metrics:
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- - accuracy
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  model-index:
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  - name: resnet-18-finetuned-fraud
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  results:
@@ -18,9 +20,9 @@ model-index:
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  split: train
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  args: default
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  metrics:
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- - name: Accuracy
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- type: accuracy
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- value: 0.6923076923076923
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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
@@ -28,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # resnet-18-finetuned-fraud
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- This model was trained from scratch on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5624
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- - Accuracy: 0.6923
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  ## Model description
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@@ -51,11 +53,11 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 32
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- - eval_batch_size: 32
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  - seed: 42
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  - gradient_accumulation_steps: 4
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- - total_train_batch_size: 128
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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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  ### 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 | 0.6821 | 0.6923 |
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- | No log | 2.0 | 4 | 0.6628 | 0.6923 |
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- | No log | 3.0 | 6 | 0.6422 | 0.6923 |
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- | No log | 4.0 | 8 | 0.6218 | 0.6923 |
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- | 0.6696 | 5.0 | 10 | 0.6059 | 0.6923 |
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- | 0.6696 | 6.0 | 12 | 0.5922 | 0.6923 |
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- | 0.6696 | 7.0 | 14 | 0.5782 | 0.6923 |
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- | 0.6696 | 8.0 | 16 | 0.5681 | 0.6923 |
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- | 0.6696 | 9.0 | 18 | 0.5620 | 0.6923 |
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- | 0.6234 | 10.0 | 20 | 0.5624 | 0.6923 |
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  ### Framework versions
 
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  ---
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+ license: apache-2.0
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+ base_model: microsoft/resnet-18
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  tags:
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  - generated_from_trainer
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  datasets:
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  - imagefolder
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  metrics:
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+ - precision
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  model-index:
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  - name: resnet-18-finetuned-fraud
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  results:
 
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  split: train
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  args: default
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  metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.0
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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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  # resnet-18-finetuned-fraud
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+ This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2060572751382446080.0000
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+ - Precision: 0.0
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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  - seed: 42
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  - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Precision |
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+ |:------------------------:|:-----:|:----:|:------------------------:|:---------:|
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+ | No log | 1.0 | 2 | 2060572751382446080.0000 | 0.0 |
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+ | No log | 2.0 | 4 | 2060572751382446080.0000 | 0.0 |
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+ | No log | 3.0 | 6 | 2060572751382446080.0000 | 0.0 |
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+ | No log | 4.0 | 8 | 2060572751382446080.0000 | 0.0 |
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+ | 2569276759331150336.0000 | 5.0 | 10 | 2060572751382446080.0000 | 0.0 |
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+ | 2569276759331150336.0000 | 6.0 | 12 | 2060572751382446080.0000 | 0.0 |
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+ | 2569276759331150336.0000 | 7.0 | 14 | 2060572751382446080.0000 | 0.0 |
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+ | 2569276759331150336.0000 | 8.0 | 16 | 2060572751382446080.0000 | 0.0 |
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+ | 2569276759331150336.0000 | 9.0 | 18 | 2060572751382446080.0000 | 0.0 |
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+ | 2411513773224361984.0000 | 10.0 | 20 | 2060572751382446080.0000 | 0.0 |
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  ### Framework versions
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