update model card README.md

README.md

@@ -1,12 +1,27 @@
 ---
-license: apache-2.0
+license: other
 tags:
 - generated_from_trainer
 datasets:
-- image_folder
+- imagefolder
+metrics:
+- accuracy
 model-index:
 - name: histo_train_segformer
-  results: []
+  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: 0.875
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -14,7 +29,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # histo_train_segformer
 
-This model is a fine-tuned version of [tcvrishank/histo_train_vit](https://huggingface.co/tcvrishank/histo_train_vit) on the image_folder dataset.
+This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3830
+- Accuracy: 0.875
 
 ## Model description
 
@@ -33,22 +51,25 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
+- learning_rate: 0.0002
 - train_batch_size: 64
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 8
+- num_epochs: 20
 - mixed_precision_training: Native AMP
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2234        | 16.67 | 100  | 0.3830          | 0.875    |
 
 
 ### Framework versions
 
-- Transformers 4.26.1
-- Pytorch 1.13.0
-- Datasets 2.1.0
+- Transformers 4.27.3
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.1
 - Tokenizers 0.13.2