update model card README.md

README.md

@@ -16,14 +16,16 @@ model-index:
     dataset:
       name: emotion
       type: emotion
-      args: default
+      config: split
+      split: validation
+      args: split
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9245
+      value: 0.9215
     - name: F1
       type: f1
-      value: 0.9246345608107297
+      value: 0.9215386837894378
 ---
 
 <!-- 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: 0.2166
-- Accuracy: 0.9245
-- F1: 0.9246
+- Loss: 0.2227
+- Accuracy: 0.9215
+- F1: 0.9215
 
 ## Model description
 
@@ -66,13 +68,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8132        | 1.0   | 250  | 0.3117          | 0.902    | 0.8990 |
-| 0.2419        | 2.0   | 500  | 0.2166          | 0.9245   | 0.9246 |
+| 0.8265        | 1.0   | 250  | 0.3204          | 0.9      | 0.8963 |
+| 0.2534        | 2.0   | 500  | 0.2227          | 0.9215   | 0.9215 |
 
 
 ### Framework versions
 
-- Transformers 4.11.3
-- Pytorch 1.10.0+cu111
-- Datasets 1.16.1
-- Tokenizers 0.10.3
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3