update model card README.md

README.md

@@ -20,10 +20,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.925
+      value: 0.9385
     - name: F1
       type: f1
-      value: 0.92522341807509
+      value: 0.9383492808338979
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,9 +33,9 @@ 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: 0.2218
-- Accuracy: 0.925
-- F1: 0.9252
+- Loss: 0.1495
+- Accuracy: 0.9385
+- F1: 0.9383
 
 ## Model description
 
@@ -60,19 +60,22 @@ 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: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8435        | 1.0   | 250  | 0.3160          | 0.9065   | 0.9045 |
-| 0.2496        | 2.0   | 500  | 0.2218          | 0.925    | 0.9252 |
+| 0.1739        | 1.0   | 250  | 0.1827          | 0.931    | 0.9302 |
+| 0.1176        | 2.0   | 500  | 0.1567          | 0.9325   | 0.9326 |
+| 0.0994        | 3.0   | 750  | 0.1555          | 0.9385   | 0.9389 |
+| 0.08          | 4.0   | 1000 | 0.1496          | 0.9445   | 0.9443 |
+| 0.0654        | 5.0   | 1250 | 0.1495          | 0.9385   | 0.9383 |
 
 
 ### Framework versions
 
-- Transformers 4.15.0
+- Transformers 4.16.0.dev0
 - Pytorch 1.10.0+cu111
-- Datasets 1.17.0
+- Datasets 1.18.0
 - Tokenizers 0.10.3