update model card README.md

README.md

@@ -16,14 +16,16 @@ model-index:
     dataset:
       name: emotion
       type: emotion
+      config: default
+      split: train
       args: default
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.92
+      value: 0.9385
     - name: F1
       type: f1
-      value: 0.9201111326949308
+      value: 0.9386094184311659
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,9 +35,9 @@ 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: 0.2174
-- Accuracy: 0.92
-- F1: 0.9201
+- Loss: 0.1635
+- Accuracy: 0.9385
+- F1: 0.9386
 
 ## Model description
 
@@ -60,19 +62,21 @@ 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: 2
+- num_epochs: 4
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.83          | 1.0   | 250  | 0.3120          | 0.905    | 0.9028 |
-| 0.2469        | 2.0   | 500  | 0.2174          | 0.92     | 0.9201 |
+| 0.1408        | 1.0   | 250  | 0.1685          | 0.93     | 0.9293 |
+| 0.0895        | 2.0   | 500  | 0.1563          | 0.936    | 0.9356 |
+| 0.0758        | 3.0   | 750  | 0.1568          | 0.9385   | 0.9388 |
+| 0.0663        | 4.0   | 1000 | 0.1635          | 0.9385   | 0.9386 |
 
 
 ### Framework versions
 
-- Transformers 4.13.0
+- Transformers 4.24.0
 - Pytorch 1.12.1+cu113
-- Datasets 1.16.1
-- Tokenizers 0.10.3
+- Datasets 2.6.1
+- Tokenizers 0.13.1