update model card README.md

README.md

@@ -5,7 +5,6 @@ tags:
 datasets:
 - emotion
 metrics:
-- accuracy
 - f1
 model-index:
 - name: distilbert-base-uncased-finetuned-emotion
@@ -18,12 +17,9 @@ model-index:
       type: emotion
       args: default
     metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.9255
     - name: F1
       type: f1
-      value: 0.9256296424769981
+      value: 0.9184567794520658
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,9 +29,9 @@ 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: 0.2148
-- Accuracy: 0.9255
-- F1: 0.9256
+- Loss: 0.2207
+- Accuracy is: 0.9185
+- F1: 0.9185
 
 ## Model description
 
@@ -64,15 +60,15 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8342        | 1.0   | 250  | 0.3147          | 0.9065   | 0.9031 |
-| 0.2502        | 2.0   | 500  | 0.2148          | 0.9255   | 0.9256 |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy is | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:-----------:|:------:|
+| 0.8026        | 1.0   | 250  | 0.3114          | 0.905       | 0.9035 |
+| 0.2409        | 2.0   | 500  | 0.2207          | 0.9185      | 0.9185 |
 
 
 ### Framework versions
 
 - Transformers 4.11.3
-- Pytorch 1.11.0+cu113
+- Pytorch 1.12.0+cu113
 - Datasets 1.16.1
 - Tokenizers 0.10.3