Training completed!

README.md

@@ -23,23 +23,23 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.925
+      value: 0.924
     - name: F1
       type: f1
-      value: 0.9247514341075832
+      value: 0.9240276037563792
 ---
 
 <!-- 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/7l1604ln)
+[<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/7lxysatn)
 # distilbert-base-uncased-finetuned-emotion
 
 This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the emotion dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2140
-- Accuracy: 0.925
-- F1: 0.9248
+- Loss: 0.2148
+- Accuracy: 0.924
+- F1: 0.9240
 
 ## Model description
 
@@ -70,8 +70,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8108        | 1.0   | 250  | 0.3094          | 0.9075   | 0.9066 |
-| 0.2435        | 2.0   | 500  | 0.2140          | 0.925    | 0.9248 |
+| 0.8356        | 1.0   | 250  | 0.3096          | 0.9085   | 0.9072 |
+| 0.2479        | 2.0   | 500  | 0.2148          | 0.924    | 0.9240 |
 
 
 ### Framework versions