update model card README.md

README.md

@@ -22,10 +22,10 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.7011856046766533
+      value: 0.7350080900694398
     - name: Recall
       type: recall
-      value: 0.70050974975592
+      value: 0.7334480130231172
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,10 +35,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the tweet_eval dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.3021
-- Precision: 0.7012
-- Recall: 0.7005
-- Fscore: 0.6995
+- Loss: 1.1951
+- Precision: 0.7350
+- Recall: 0.7334
+- Fscore: 0.7341
 
 ## Model description
 
@@ -69,9 +69,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Fscore |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
-| 0.8733        | 1.0   | 815  | 0.7449          | 0.7633    | 0.6434 | 0.6701 |
-| 0.5616        | 2.0   | 1630 | 1.0488          | 0.7170    | 0.6607 | 0.6818 |
-| 0.3055        | 3.0   | 2445 | 1.3021          | 0.7012    | 0.7005 | 0.6995 |
+| 0.8468        | 1.0   | 815  | 0.7465          | 0.7116    | 0.6096 | 0.6325 |
+| 0.5105        | 2.0   | 1630 | 0.9035          | 0.7532    | 0.7111 | 0.7276 |
+| 0.2492        | 3.0   | 2445 | 1.1951          | 0.7350    | 0.7334 | 0.7341 |
 
 
 ### Framework versions