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nosql-identifier-distilbert

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ankush-003 commited on Jul 26, 2023

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update model card README.md

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@@ -17,8 +17,8 @@ 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 an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2224
-- Accuracy: 0.925
 ## Model description
@@ -43,22 +43,27 @@ 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: 10
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 40   | 0.5824          | 0.575    |
-| No log        | 2.0   | 80   | 0.3768          | 0.95     |
-| No log        | 3.0   | 120  | 0.2381          | 0.925    |
-| No log        | 4.0   | 160  | 0.2721          | 0.9      |
-| No log        | 5.0   | 200  | 0.1597          | 0.95     |
-| No log        | 6.0   | 240  | 0.2096          | 0.95     |
-| No log        | 7.0   | 280  | 0.4053          | 0.825    |
-| No log        | 8.0   | 320  | 0.2440          | 0.9      |
-| No log        | 9.0   | 360  | 0.2514          | 0.9      |
-| No log        | 10.0  | 400  | 0.2224          | 0.925    |
 ### Framework versions

 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.1660
+- Accuracy: 0.95
 ## Model description
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
+- num_epochs: 15
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 40   | 0.4882          | 0.875    |
+| No log        | 2.0   | 80   | 0.2036          | 0.975    |
+| No log        | 3.0   | 120  | 0.1521          | 0.975    |
+| No log        | 4.0   | 160  | 0.2719          | 0.875    |
+| No log        | 5.0   | 200  | 0.0980          | 0.975    |
+| No log        | 6.0   | 240  | 0.1752          | 0.95     |
+| No log        | 7.0   | 280  | 0.3715          | 0.9      |
+| No log        | 8.0   | 320  | 0.1640          | 0.95     |
+| No log        | 9.0   | 360  | 0.1756          | 0.95     |
+| No log        | 10.0  | 400  | 0.1386          | 0.975    |
+| No log        | 11.0  | 440  | 0.2747          | 0.95     |
+| No log        | 12.0  | 480  | 0.2302          | 0.95     |
+| 0.2758        | 13.0  | 520  | 0.2518          | 0.95     |
+| 0.2758        | 14.0  | 560  | 0.1722          | 0.95     |
+| 0.2758        | 15.0  | 600  | 0.1660          | 0.95     |
 ### Framework versions