update model card README.md

README.md

@@ -2,26 +2,11 @@
 license: mit
 tags:
 - generated_from_trainer
-datasets:
-- feverous
 metrics:
 - accuracy
 model-index:
 - name: deberta-v3-base-finetuned-fever
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: feverous
-      type: feverous
-      config: default
-      split: validation
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.6153358681875792
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # deberta-v3-base-finetuned-fever
 
-This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the feverous dataset.
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8830
-- Accuracy: 0.6153
+- Loss: 1.0792
+- Accuracy: 0.4965
 
 ## Model description
 
@@ -52,8 +37,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 2
+- eval_batch_size: 2
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -61,13 +46,13 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
-|:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 0.7054        | 1.0   | 4456  | 0.8351          | 0.6027   |
-| 0.6389        | 2.0   | 8912  | 0.8830          | 0.6153   |
-| 0.5562        | 3.0   | 13368 | 0.9398          | 0.6134   |
-| 0.4614        | 4.0   | 17824 | 1.0787          | 0.6115   |
-| 0.3867        | 5.0   | 22280 | 1.1430          | 0.6091   |
+| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
+|:-------------:|:-----:|:------:|:---------------:|:--------:|
+| 0.8873        | 1.0   | 20000  | 1.0792          | 0.4965   |
+| 0.8178        | 2.0   | 40000  | 1.4091          | 0.4965   |
+| 0.7809        | 3.0   | 60000  | 1.4333          | 0.4965   |
+| 0.7748        | 4.0   | 80000  | 1.3670          | 0.4965   |
+| 0.825         | 5.0   | 100000 | 1.3884          | 0.4965   |
 
 
 ### Framework versions