update model card README.md

README.md

@@ -0,0 +1,85 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: efficientnet-b5-Brain_Tumors_Image_Classification
+  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: 0.8020304568527918
+---
+
+<!-- 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. -->
+
+# efficientnet-b5-Brain_Tumors_Image_Classification
+
+This model is a fine-tuned version of [google/efficientnet-b5](https://huggingface.co/google/efficientnet-b5) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9410
+- Accuracy: 0.8020
+- Weighted f1: 0.7736
+- Micro f1: 0.8020
+- Macro f1: 0.7802
+- Weighted recall: 0.8020
+- Micro recall: 0.8020
+- Macro recall: 0.7977
+- Weighted precision: 0.8535
+- Micro precision: 0.8020
+- Macro precision: 0.8682
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
+| 1.3872        | 1.0   | 180  | 1.0601          | 0.6853   | 0.6485      | 0.6853   | 0.6550   | 0.6853          | 0.6853       | 0.6802       | 0.8177             | 0.6853          | 0.8330          |
+| 1.3872        | 2.0   | 360  | 0.9533          | 0.7843   | 0.7483      | 0.7843   | 0.7548   | 0.7843          | 0.7843       | 0.7819       | 0.8354             | 0.7843          | 0.8471          |
+| 0.8186        | 3.0   | 540  | 0.9410          | 0.8020   | 0.7736      | 0.8020   | 0.7802   | 0.8020          | 0.8020       | 0.7977       | 0.8535             | 0.8020          | 0.8682          |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0
+- Datasets 2.11.0
+- Tokenizers 0.13.3