update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.20394736842105263
+      value: 0.34523809523809523
     - name: Recall
       type: recall
-      value: 0.2897196261682243
+      value: 0.5420560747663551
     - name: F1
       type: f1
-      value: 0.23938223938223938
+      value: 0.4218181818181818
     - name: Accuracy
       type: accuracy
-      value: 0.817741935483871
+      value: 0.8688172043010752
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,11 +43,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the wikiann dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6372
-- Precision: 0.2039
-- Recall: 0.2897
-- F1: 0.2394
-- Accuracy: 0.8177
+- Loss: 0.5677
+- Precision: 0.3452
+- Recall: 0.5421
+- F1: 0.4218
+- Accuracy: 0.8688
 
 ## Model description
 
@@ -72,15 +72,22 @@ 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: 3
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 13   | 0.7383          | 0.1463    | 0.1121 | 0.1270 | 0.7737   |
-| No log        | 2.0   | 26   | 0.6586          | 0.1618    | 0.2056 | 0.1811 | 0.8075   |
-| No log        | 3.0   | 39   | 0.6372          | 0.2039    | 0.2897 | 0.2394 | 0.8177   |
+| No log        | 1.0   | 13   | 0.5728          | 0.2077    | 0.3551 | 0.2621 | 0.8199   |
+| No log        | 2.0   | 26   | 0.5687          | 0.2889    | 0.3645 | 0.3223 | 0.8312   |
+| No log        | 3.0   | 39   | 0.5447          | 0.2857    | 0.4486 | 0.3491 | 0.8425   |
+| No log        | 4.0   | 52   | 0.5509          | 0.2881    | 0.4766 | 0.3592 | 0.8489   |
+| No log        | 5.0   | 65   | 0.5751          | 0.3121    | 0.4579 | 0.3712 | 0.8511   |
+| No log        | 6.0   | 78   | 0.5358          | 0.3851    | 0.5794 | 0.4627 | 0.8667   |
+| No log        | 7.0   | 91   | 0.5484          | 0.3491    | 0.5514 | 0.4275 | 0.8645   |
+| No log        | 8.0   | 104  | 0.5671          | 0.3580    | 0.5421 | 0.4312 | 0.8672   |
+| No log        | 9.0   | 117  | 0.5666          | 0.3494    | 0.5421 | 0.4249 | 0.8688   |
+| No log        | 10.0  | 130  | 0.5677          | 0.3452    | 0.5421 | 0.4218 | 0.8688   |
 
 
 ### Framework versions