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: plant-seedlings-freeze-0-6-aug-3-lr-decay
+  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: 0.81286836935167
+---
+
+<!-- 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. -->
+
+# plant-seedlings-freeze-0-6-aug-3-lr-decay
+
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5661
+- Accuracy: 0.8129
+
+## 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: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 13
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5566        | 1.59  | 100  | 0.5549          | 0.8193   |
+| 0.4338        | 3.17  | 200  | 0.5507          | 0.8212   |
+| 0.4637        | 4.76  | 300  | 0.5418          | 0.8193   |
+| 0.5061        | 6.35  | 400  | 0.5586          | 0.8139   |
+| 0.3512        | 7.94  | 500  | 0.5550          | 0.8291   |
+| 0.4779        | 9.52  | 600  | 0.5414          | 0.8256   |
+| 0.449         | 11.11 | 700  | 0.5815          | 0.8055   |
+| 0.5039        | 12.7  | 800  | 0.5661          | 0.8129   |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.3