update model card README.md

README.md

@@ -4,34 +4,9 @@ tags:
 - generated_from_trainer
 datasets:
 - consumer-finance-complaints
-metrics:
-- accuracy
-- f1
-- recall
-- precision
 model-index:
 - name: distilbert-base-uncased-wandb-week-3-complaints-classifier-1500
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: consumer-finance-complaints
-      type: consumer-finance-complaints
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.8210081035625095
-    - name: F1
-      type: f1
-      value: 0.8181860806077187
-    - name: Recall
-      type: recall
-      value: 0.8210081035625095
-    - name: Precision
-      type: precision
-      value: 0.8187295355668672
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,12 +15,6 @@ should probably proofread and complete it, then remove this comment. -->
 # distilbert-base-uncased-wandb-week-3-complaints-classifier-1500
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the consumer-finance-complaints dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5521
-- Accuracy: 0.8210
-- F1: 0.8182
-- Recall: 0.8210
-- Precision: 0.8187
 
 ## Model description
 
@@ -76,10 +45,6 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
-| 0.7063        | 0.82  | 2000 | 0.6899          | 0.7809   | 0.7544 | 0.7809 | 0.7646    |
-| 0.505         | 1.63  | 4000 | 0.5521          | 0.8210   | 0.8182 | 0.8210 | 0.8187    |
 
 
 ### Framework versions