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_two_classes
+  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: 0.85
+---
+
+<!-- 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_two_classes
+
+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: 0.4531
+- Accuracy: 0.85
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5955        | 1.0   | 13   | 0.4665          | 0.85     |
+| 0.5303        | 2.0   | 26   | 0.4790          | 0.85     |
+| 0.6127        | 3.0   | 39   | 0.4787          | 0.85     |
+| 0.5025        | 4.0   | 52   | 0.4547          | 0.85     |
+| 0.471         | 5.0   | 65   | 0.4621          | 0.85     |
+| 0.4673        | 6.0   | 78   | 0.4775          | 0.86     |
+| 0.4492        | 7.0   | 91   | 0.4648          | 0.86     |
+| 0.4144        | 8.0   | 104  | 0.4733          | 0.85     |
+| 0.4963        | 9.0   | 117  | 0.4575          | 0.85     |
+| 0.4149        | 10.0  | 130  | 0.4691          | 0.85     |
+| 0.4588        | 11.0  | 143  | 0.4596          | 0.84     |
+| 0.3995        | 12.0  | 156  | 0.4754          | 0.85     |
+| 0.359         | 13.0  | 169  | 0.4616          | 0.85     |
+| 0.4246        | 14.0  | 182  | 0.4552          | 0.85     |
+| 0.4001        | 15.0  | 195  | 0.4839          | 0.85     |
+| 0.3919        | 16.0  | 208  | 0.4708          | 0.85     |
+| 0.4137        | 17.0  | 221  | 0.4416          | 0.85     |
+| 0.3912        | 18.0  | 234  | 0.4507          | 0.85     |
+| 0.4322        | 19.0  | 247  | 0.4237          | 0.85     |
+| 0.4043        | 20.0  | 260  | 0.4531          | 0.85     |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

model.safetensors

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