update model card README.md

README.md

@@ -4,9 +4,28 @@ tags:
 - generated_from_trainer
 datasets:
 - imdb
+metrics:
+- accuracy
+- f1
 model-index:
 - name: finetuning-sentiment-model-3000-samples
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: imdb
+      type: imdb
+      config: plain_text
+      split: train
+      args: plain_text
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8675
+    - name: F1
+      type: f1
+      value: 0.8704156479217605
 ---
 
 <!-- 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-sentiment-model-3000-samples
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3861
+- Accuracy: 0.8675
+- F1: 0.8704
 
 ## Model description
 
@@ -33,13 +56,13 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 0.0002
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 2
+- num_epochs: 3
 
 ### Training results