update model card README.md

README.md

@@ -4,9 +4,28 @@ tags:
 - generated_from_trainer
 datasets:
 - emotion
+metrics:
+- accuracy
+- f1
 model-index:
 - name: finetuning-emotion-model
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: emotion
+      type: emotion
+      config: split
+      split: validation
+      args: split
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9205
+    - name: F1
+      type: f1
+      value: 0.9204323723383444
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,6 +34,10 @@ should probably proofread and complete it, then remove this comment. -->
 # finetuning-emotion-model
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2238
+- Accuracy: 0.9205
+- F1: 0.9204
 
 ## Model description
 
@@ -39,13 +62,14 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 1
+- num_epochs: 2
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| No log        | 1.0   | 250  | 0.5276          | 0.8415   | 0.8254 |
+| No log        | 1.0   | 250  | 0.3235          | 0.9035   | 0.9003 |
+| 0.5384        | 2.0   | 500  | 0.2238          | 0.9205   | 0.9204 |
 
 
 ### Framework versions