update model card README.md

README.md

@@ -2,28 +2,12 @@
 license: mit
 tags:
 - generated_from_trainer
-datasets:
-- tweet_eval
 metrics:
 - accuracy
 - f1
 model-index:
 - name: tweet_eval-sentiment-finetuned
-  results: 
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: sentiment
-      type: sentiment
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.70
-    - name: f1
-      type: f1
-      value: 0.70
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,11 +15,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # tweet_eval-sentiment-finetuned
 
-This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the tweet_eval dataset.
+This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8369
-- Accuracy: 0.7305
-- F1: 0.7297
+- Loss: 0.6532
+- Accuracy: 0.744
+- F1: 0.7437
 
 ## Model description
 
@@ -54,7 +38,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 8e-05
+- learning_rate: 3e-05
 - train_batch_size: 128
 - eval_batch_size: 256
 - seed: 42
@@ -68,10 +52,10 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.7269        | 1.0   | 357  | 0.6057          | 0.733    | 0.7323 |
-| 0.522         | 2.0   | 714  | 0.6115          | 0.7415   | 0.7416 |
-| 0.359         | 3.0   | 1071 | 0.6970          | 0.744    | 0.7445 |
-| 0.2386        | 4.0   | 1428 | 0.8369          | 0.7305   | 0.7297 |
+| 0.7491        | 1.0   | 357  | 0.6089          | 0.7345   | 0.7314 |
+| 0.5516        | 2.0   | 714  | 0.5958          | 0.751    | 0.7516 |
+| 0.4618        | 3.0   | 1071 | 0.6131          | 0.748    | 0.7487 |
+| 0.4066        | 4.0   | 1428 | 0.6532          | 0.744    | 0.7437 |
 
 
 ### Framework versions