End of training

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 1.0
+      value: 0.5583832335329342
     - name: Recall
       type: recall
-      value: 1.0
+      value: 0.520949720670391
     - name: F1
       type: f1
-      value: 1.0
+      value: 0.5390173410404625
     - name: Accuracy
       type: accuracy
-      value: 1.0
+      value: 0.9721157973387596
 ---
 
 <!-- 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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the indian_names dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0
-- Precision: 1.0
-- Recall: 1.0
-- F1: 1.0
-- Accuracy: 1.0
+- Loss: 0.1028
+- Precision: 0.5584
+- Recall: 0.5209
+- F1: 0.5390
+- Accuracy: 0.9721
 
 ## 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   | 1    | 0.0             | 1.0       | 1.0    | 1.0 | 1.0      |
-| No log        | 2.0   | 2    | 0.0             | 1.0       | 1.0    | 1.0 | 1.0      |
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 213  | 0.1348          | 0.4605    | 0.3613 | 0.4049 | 0.9633   |
+| No log        | 2.0   | 426  | 0.1028          | 0.5584    | 0.5209 | 0.5390 | 0.9721   |
 
 
 ### Framework versions