End of training

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 1.0
+      value: 0.9863945578231292
     - name: Recall
       type: recall
-      value: 1.0
+      value: 0.9954233409610984
     - name: F1
       type: f1
-      value: 1.0
+      value: 0.9908883826879271
     - name: Accuracy
       type: accuracy
-      value: 1.0
+      value: 0.9953216374269006
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [dslim/bert-large-NER](https://huggingface.co/dslim/bert-large-NER) on the job-titles dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0027
-- Precision: 1.0
-- Recall: 1.0
-- F1: 1.0
-- Accuracy: 1.0
+- Loss: 0.0080
+- Precision: 0.9864
+- Recall: 0.9954
+- F1: 0.9909
+- Accuracy: 0.9953
 
 ## Model description
 
@@ -77,10 +77,10 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
-| No log        | 1.0   | 18   | 0.0139          | 1.0       | 1.0    | 1.0 | 1.0      |
-| No log        | 2.0   | 36   | 0.0027          | 1.0       | 1.0    | 1.0 | 1.0      |
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 18   | 0.0232          | 0.9864    | 0.9954 | 0.9909 | 0.9953   |
+| No log        | 2.0   | 36   | 0.0080          | 0.9864    | 0.9954 | 0.9909 | 0.9953   |
 
 
 ### Framework versions