Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/resnet-50
+tags:
+- generated_from_trainer
+datasets:
+- cats_vs_dogs
+metrics:
+- accuracy
+model-index:
+- name: resnet-50-finetuned-dog-vs-cat
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: cats_vs_dogs
+      type: cats_vs_dogs
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9918838103374626
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# resnet-50-finetuned-dog-vs-cat
+
+This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the cats_vs_dogs dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0460
+- Accuracy: 0.9919
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3357        | 1.0   | 164  | 0.2255          | 0.9868   |
+| 0.1683        | 2.0   | 329  | 0.0577          | 0.9919   |
+| 0.1448        | 2.99  | 492  | 0.0460          | 0.9919   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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