update model card README.md

README.md

@@ -1,5 +1,5 @@
 ---
-license: apache-2.0
+license: mit
 tags:
 - generated_from_trainer
 datasets:
@@ -20,10 +20,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.86
+      value: 0.9133333333333333
     - name: F1
       type: f1
-      value: 0.8636363636363636
+      value: 0.9144736842105262
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,11 +31,11 @@ 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.
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the imdb dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2972
-- Accuracy: 0.86
-- F1: 0.8636
+- Loss: 0.4325
+- Accuracy: 0.9133
+- F1: 0.9145
 
 ## Model description
 
@@ -54,13 +54,13 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 8e-05
 - 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: 6
 
 ### Training results