update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: resnet-50-finetuned-resnet50_0831
+  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: 0.976407675369613
+---
+
+<!-- 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-resnet50_0831
+
+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: 0.0862
+- Accuracy: 0.9764
+
+## 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: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.9066        | 1.0   | 223  | 0.8770          | 0.6659   |
+| 0.5407        | 2.0   | 446  | 0.4251          | 0.7867   |
+| 0.3614        | 3.0   | 669  | 0.2009          | 0.9390   |
+| 0.3016        | 4.0   | 892  | 0.1362          | 0.9582   |
+| 0.2358        | 5.0   | 1115 | 0.1139          | 0.9676   |
+| 0.247         | 6.0   | 1338 | 0.1081          | 0.9698   |
+| 0.2135        | 7.0   | 1561 | 0.1027          | 0.9720   |
+| 0.2043        | 8.0   | 1784 | 0.1026          | 0.9695   |
+| 0.2165        | 9.0   | 2007 | 0.0957          | 0.9733   |
+| 0.1983        | 10.0  | 2230 | 0.0936          | 0.9736   |
+| 0.2116        | 11.0  | 2453 | 0.0949          | 0.9736   |
+| 0.2341        | 12.0  | 2676 | 0.0905          | 0.9755   |
+| 0.2004        | 13.0  | 2899 | 0.0901          | 0.9739   |
+| 0.1956        | 14.0  | 3122 | 0.0877          | 0.9755   |
+| 0.1668        | 15.0  | 3345 | 0.0847          | 0.9764   |
+| 0.1855        | 16.0  | 3568 | 0.0850          | 0.9755   |
+| 0.18          | 17.0  | 3791 | 0.0897          | 0.9745   |
+| 0.1772        | 18.0  | 4014 | 0.0852          | 0.9755   |
+| 0.1881        | 19.0  | 4237 | 0.0845          | 0.9764   |
+| 0.2145        | 20.0  | 4460 | 0.0862          | 0.9764   |
+
+
+### Framework versions
+
+- Transformers 4.21.1
+- Pytorch 1.12.1
+- Datasets 2.4.0
+- Tokenizers 0.12.1