update model card README.md

README.md

@@ -2,28 +2,12 @@
 license: apache-2.0
 tags:
 - generated_from_trainer
-datasets:
-- emotion
 metrics:
 - accuracy
 - f1
 model-index:
 - name: distilbert-base-uncased-finetuned-emotion
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: emotion
-      type: emotion
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.927
-    - name: F1
-      type: f1
-      value: 0.9272852513255202
+  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. -->
 
 # 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.
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2171
-- Accuracy: 0.927
-- F1: 0.9273
+- Loss: 0.1995
+- Accuracy: 0.9365
+- F1: 0.9371
 
 ## Model description
 
@@ -60,14 +44,17 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 2
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8357        | 1.0   | 250  | 0.3131          | 0.911    | 0.9080 |
-| 0.2536        | 2.0   | 500  | 0.2171          | 0.927    | 0.9273 |
+| 0.475         | 1.0   | 503  | 0.2171          | 0.928    | 0.9292 |
+| 0.1235        | 2.0   | 1006 | 0.1764          | 0.9365   | 0.9372 |
+| 0.0802        | 3.0   | 1509 | 0.1788          | 0.938    | 0.9388 |
+| 0.0531        | 4.0   | 2012 | 0.2005          | 0.938    | 0.9388 |
+| 0.0367        | 5.0   | 2515 | 0.1995          | 0.9365   | 0.9371 |
 
 
 ### Framework versions