End of training

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 1.0
+      value: 0.980007544322897
     - name: Recall
       type: recall
-      value: 1.0
+      value: 0.979145728643216
     - name: F1
       type: f1
-      value: 1.0
+      value: 0.9795764469301829
     - name: Accuracy
       type: accuracy
-      value: 1.0
+      value: 0.9962591162591162
 ---
 
 <!-- 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: 0.0035
-- Precision: 1.0
-- Recall: 1.0
-- F1: 1.0
-- Accuracy: 1.0
+- Loss: 0.0148
+- Precision: 0.9800
+- Recall: 0.9791
+- F1: 0.9796
+- Accuracy: 0.9963
 
 ## Model description
 
@@ -73,17 +73,22 @@ 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: 5
+- num_epochs: 10
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
-| No log        | 1.0   | 1    | 0.2174          | 1.0       | 1.0    | 1.0 | 1.0      |
-| No log        | 2.0   | 2    | 0.0553          | 1.0       | 1.0    | 1.0 | 1.0      |
-| No log        | 3.0   | 3    | 0.0124          | 1.0       | 1.0    | 1.0 | 1.0      |
-| No log        | 4.0   | 4    | 0.0048          | 1.0       | 1.0    | 1.0 | 1.0      |
-| No log        | 5.0   | 5    | 0.0035          | 1.0       | 1.0    | 1.0 | 1.0      |
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 66   | 0.1644          | 0.1903    | 0.1692 | 0.1791 | 0.8817   |
+| No log        | 2.0   | 132  | 0.1154          | 0.9760    | 0.8181 | 0.8901 | 0.9703   |
+| No log        | 3.0   | 198  | 0.0921          | 0.9755    | 0.9046 | 0.9387 | 0.9795   |
+| No log        | 4.0   | 264  | 0.0586          | 0.9616    | 0.9193 | 0.9400 | 0.9849   |
+| No log        | 5.0   | 330  | 0.0465          | 0.9588    | 0.9219 | 0.9400 | 0.9861   |
+| No log        | 6.0   | 396  | 0.0346          | 0.9359    | 0.9460 | 0.9409 | 0.9902   |
+| No log        | 7.0   | 462  | 0.0227          | 0.9708    | 0.9678 | 0.9693 | 0.9941   |
+| 0.1068        | 8.0   | 528  | 0.0199          | 0.9753    | 0.9734 | 0.9743 | 0.9946   |
+| 0.1068        | 9.0   | 594  | 0.0155          | 0.9801    | 0.9784 | 0.9793 | 0.9961   |
+| 0.1068        | 10.0  | 660  | 0.0148          | 0.9800    | 0.9791 | 0.9796 | 0.9963   |
 
 
 ### Framework versions