End of training

README.md

@@ -19,7 +19,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.917
+      value: 0.9295
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,8 +29,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 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: 0.2502
-- Accuracy: 0.917
+- Loss: 0.1501
+- Accuracy: 0.9295
 
 ## Model description
 
@@ -56,14 +56,16 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- num_epochs: 1
+- num_epochs: 3
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.9571        | 1.0   | 500  | 0.2502          | 0.917    |
+| 0.9265        | 1.0   | 500  | 0.2448          | 0.9175   |
+| 0.1855        | 2.0   | 1000 | 0.1660          | 0.9245   |
+| 0.1017        | 3.0   | 1500 | 0.1501          | 0.9295   |
 
 
 ### Framework versions