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NiharGupte
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resnet-50-finetuned-student_kaggle

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  1. README.md +10 -12
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.4889937106918239
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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
@@ -32,8 +32,8 @@ 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: 34897389209777069883392.0000
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- - Accuracy: 0.4890
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  ## Model description
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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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- | 33718936798882659565568.0000 | 0.9362 | 11 | 34897389209777069883392.0000 | 0.4890 |
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- | 32438469749948979085312.0000 | 1.9574 | 23 | 34897389209777069883392.0000 | 0.4890 |
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- | 33363246103192638849024.0000 | 2.9787 | 35 | 34897389209777069883392.0000 | 0.4890 |
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- | 32954207567756639862784.0000 | 4.0 | 47 | 34897389209777069883392.0000 | 0.4890 |
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- | 32794156842759294550016.0000 | 4.6809 | 55 | 34897389209777069883392.0000 | 0.4890 |
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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: 0.9874213836477987
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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: 0.0354
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+ - Accuracy: 0.9874
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  ## Model description
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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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  - 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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+ | 0.5044 | 1.0 | 47 | 0.2463 | 0.8978 |
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+ | 0.2076 | 2.0 | 94 | 0.1007 | 0.9717 |
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+ | 0.2115 | 3.0 | 141 | 0.0480 | 0.9874 |
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+ | 0.1361 | 4.0 | 188 | 0.0387 | 0.9874 |
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+ | 0.1359 | 5.0 | 235 | 0.0354 | 0.9874 |
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  ### Framework versions
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