Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/resnet-50
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: resnet-50-finetuned-student_kaggle
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 1.0
+---
+
+<!-- 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-student_kaggle
+
+This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0012
+- Accuracy: 1.0
+
+## 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
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.7142        | 1.0   | 47   | 0.6418          | 0.6101   |
+| 0.3351        | 2.0   | 94   | 0.2597          | 0.8947   |
+| 0.2574        | 3.0   | 141  | 0.1046          | 0.9780   |
+| 0.1479        | 4.0   | 188  | 0.0616          | 0.9874   |
+| 0.1284        | 5.0   | 235  | 0.0232          | 0.9953   |
+| 0.077         | 6.0   | 282  | 0.0150          | 0.9953   |
+| 0.103         | 7.0   | 329  | 0.0105          | 0.9984   |
+| 0.0922        | 8.0   | 376  | 0.0094          | 0.9984   |
+| 0.08          | 9.0   | 423  | 0.0056          | 1.0      |
+| 0.0492        | 10.0  | 470  | 0.0045          | 1.0      |
+| 0.0574        | 11.0  | 517  | 0.0043          | 1.0      |
+| 0.0382        | 12.0  | 564  | 0.0023          | 1.0      |
+| 0.0666        | 13.0  | 611  | 0.0022          | 1.0      |
+| 0.0477        | 14.0  | 658  | 0.0022          | 1.0      |
+| 0.0614        | 15.0  | 705  | 0.0023          | 1.0      |
+| 0.0282        | 16.0  | 752  | 0.0014          | 1.0      |
+| 0.0659        | 17.0  | 799  | 0.0016          | 1.0      |
+| 0.0586        | 18.0  | 846  | 0.0010          | 1.0      |
+| 0.0557        | 19.0  | 893  | 0.0013          | 1.0      |
+| 0.07          | 20.0  | 940  | 0.0012          | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

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