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: efficientformer-l3-300-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: 0.7817258883248731
+---
+
+<!-- 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. -->
+
+# efficientformer-l3-300-Brain_Tumors_Image_Classification
+
+This model is a fine-tuned version of [snap-research/efficientformer-l3-300](https://huggingface.co/snap-research/efficientformer-l3-300) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.2761
+- Accuracy: 0.7817
+- Weighted f1: 0.7381
+- Micro f1: 0.7817
+- Macro f1: 0.7465
+- Weighted recall: 0.7817
+- Micro recall: 0.7817
+- Macro recall: 0.7771
+- Weighted precision: 0.8442
+- Micro precision: 0.7817
+- Macro precision: 0.8613
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
+| 1.2856        | 1.0   | 180  | 1.4677          | 0.7284   | 0.6798      | 0.7284   | 0.6829   | 0.7284          | 0.7284       | 0.7133       | 0.8156             | 0.7284          | 0.8350          |
+| 1.2856        | 2.0   | 360  | 2.1421          | 0.7563   | 0.7146      | 0.7563   | 0.7211   | 0.7563          | 0.7563       | 0.7471       | 0.8381             | 0.7563          | 0.8551          |
+| 0.1405        | 3.0   | 540  | 2.2761          | 0.7817   | 0.7381      | 0.7817   | 0.7465   | 0.7817          | 0.7817       | 0.7771       | 0.8442             | 0.7817          | 0.8613          |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0
+- Datasets 2.11.0
+- Tokenizers 0.13.3