update model card README.md

README.md

@@ -4,8 +4,6 @@ tags:
 - generated_from_trainer
 metrics:
 - accuracy
-widget:
-- '全国高校科研质量排名，清华北大浙大无缘前五。'
 model-index:
 - name: classification_tnews_scarce_imbalanced
   results: []
@@ -16,9 +14,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 # classification_tnews_scarce_imbalanced
 
-This model is a fine-tuned version of [hfl/chinese-roberta-wwm-ext](https://huggingface.co/hfl/chinese-roberta-wwm-ext) on a very small & imbalanced subset of TNews dataset.
+This model is a fine-tuned version of [hfl/chinese-roberta-wwm-ext](https://huggingface.co/hfl/chinese-roberta-wwm-ext) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5812
+- Loss: 1.8763
 - Accuracy: 0.5867
 
 ## Model description
@@ -50,16 +48,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.4743        | 1.0   | 15   | 2.5030          | 0.24     |
-| 2.1581        | 2.0   | 30   | 2.2729          | 0.4533   |
-| 1.7781        | 3.0   | 45   | 2.0809          | 0.5267   |
-| 1.5336        | 4.0   | 60   | 1.9246          | 0.5333   |
-| 1.2713        | 5.0   | 75   | 1.8133          | 0.54     |
-| 1.1           | 6.0   | 90   | 1.7276          | 0.5667   |
-| 0.9569        | 7.0   | 105  | 1.6676          | 0.5733   |
-| 0.8755        | 8.0   | 120  | 1.6177          | 0.5867   |
-| 0.7461        | 9.0   | 135  | 1.5917          | 0.5867   |
-| 0.7229        | 10.0  | 150  | 1.5812          | 0.5867   |
+| 2.7407        | 1.0   | 15   | 2.6972          | 0.1267   |
+| 2.476         | 2.0   | 30   | 2.5490          | 0.2467   |
+| 2.1124        | 3.0   | 45   | 2.4033          | 0.4067   |
+| 1.8335        | 4.0   | 60   | 2.2475          | 0.4867   |
+| 1.5516        | 5.0   | 75   | 2.1290          | 0.5333   |
+| 1.3702        | 6.0   | 90   | 2.0374          | 0.5667   |
+| 1.1347        | 7.0   | 105  | 1.9598          | 0.5733   |
+| 1.1171        | 8.0   | 120  | 1.9145          | 0.58     |
+| 0.9873        | 9.0   | 135  | 1.8869          | 0.5867   |
+| 0.9644        | 10.0  | 150  | 1.8763          | 0.5867   |
 
 
 ### Framework versions