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README.md

@@ -23,23 +23,23 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9205
+      value: 0.923
     - name: F1
       type: f1
-      value: 0.9206794124018374
+      value: 0.9230993392408946
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/wzy_study/huggingface/runs/ggpjqrrn)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/wzy_study/huggingface/runs/15gg4p6x)
 # distilbert-base-uncased-finetuned-emotion
 
 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: 0.2168
-- Accuracy: 0.9205
-- F1: 0.9207
+- Loss: 0.2147
+- Accuracy: 0.923
+- F1: 0.9231
 
 ## Model description
 
@@ -70,13 +70,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8052        | 1.0   | 250  | 0.3082          | 0.9105   | 0.9103 |
-| 0.2458        | 2.0   | 500  | 0.2168          | 0.9205   | 0.9207 |
+| 0.7996        | 1.0   | 250  | 0.3066          | 0.9115   | 0.9110 |
+| 0.2465        | 2.0   | 500  | 0.2147          | 0.923    | 0.9231 |
 
 
 ### Framework versions
 
 - Transformers 4.42.3
-- Pytorch 2.1.2+cu121
+- Pytorch 2.1.0+cu118
 - Datasets 2.20.0
 - Tokenizers 0.19.1