update model card README.md

README.md

@@ -22,10 +22,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9245
+      value: 0.938
     - name: F1
       type: f1
-      value: 0.9242943165882364
+      value: 0.9380493958812126
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,9 +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: 0.2139
-- Accuracy: 0.9245
-- F1: 0.9243
+- Loss: 0.1828
+- Accuracy: 0.938
+- F1: 0.9380
 
 ## Model description
 
@@ -57,8 +57,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 64
-- eval_batch_size: 64
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -68,13 +68,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8382        | 1.0   | 250  | 0.3038          | 0.9005   | 0.8973 |
-| 0.2437        | 2.0   | 500  | 0.2139          | 0.9245   | 0.9243 |
+| 0.421         | 1.0   | 2000 | 0.2256          | 0.926    | 0.9259 |
+| 0.155         | 2.0   | 4000 | 0.1828          | 0.938    | 0.9380 |
 
 
 ### Framework versions
 
 - Transformers 4.28.1
-- Pytorch 2.0.0+cu117
-- Datasets 1.16.1
+- Pytorch 1.11.0+cu113
+- Datasets 2.11.0
 - Tokenizers 0.13.3