update model card README.md

README.md

@@ -5,9 +5,36 @@ tags:
 - generated_from_trainer
 datasets:
 - azaheadhealth
+metrics:
+- accuracy
+- f1
+- precision
+- recall
 model-index:
 - name: microtest
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: azaheadhealth
+      type: azaheadhealth
+      config: micro
+      split: test
+      args: micro
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 1.0
+    - name: F1
+      type: f1
+      value: 1.0
+    - name: Precision
+      type: precision
+      value: 1.0
+    - name: Recall
+      type: recall
+      value: 1.0
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +43,12 @@ should probably proofread and complete it, then remove this comment. -->
 # microtest
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the azaheadhealth dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6111
+- Accuracy: 1.0
+- F1: 1.0
+- Precision: 1.0
+- Recall: 1.0
 
 ## Model description
 
@@ -35,17 +68,21 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 2
-- eval_batch_size: 2
+- train_batch_size: 1
+- eval_batch_size: 1
 - seed: 42
 - gradient_accumulation_steps: 2
-- total_train_batch_size: 4
+- total_train_batch_size: 2
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 1
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1  | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:---------:|:------:|
+| 0.5955        | 0.5   | 1    | 0.6676          | 0.5      | 0.5 | 0.5       | 0.5    |
+| 0.633         | 1.0   | 2    | 0.6111          | 1.0      | 1.0 | 1.0       | 1.0    |
 
 
 ### Framework versions