roscoyoon
/

distilbert-base-uncased-distilled

Text Classification

Generated from Trainer

Inference Endpoints

Model card Files Files and versions Community

roscoyoon commited on Aug 11, 2022

Commit

382fc18

•

1 Parent(s): 072df53

update model card README.md

Files changed (1) hide show

README.md +13 -13

README.md CHANGED Viewed

@@ -19,7 +19,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9319354838709677
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,8 +29,8 @@ 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 the clinc_oos dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0323
-- Accuracy: 0.9319
 ## Model description
@@ -61,16 +61,16 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.8025        | 1.0   | 318  | 0.4069          | 0.6610   |
-| 0.3064        | 2.0   | 636  | 0.1401          | 0.8374   |
-| 0.1407        | 3.0   | 954  | 0.0706          | 0.9087   |
-| 0.09          | 4.0   | 1272 | 0.0509          | 0.9184   |
-| 0.0704        | 5.0   | 1590 | 0.0431          | 0.9235   |
-| 0.0605        | 6.0   | 1908 | 0.0382          | 0.9297   |
-| 0.0547        | 7.0   | 2226 | 0.0356          | 0.9290   |
-| 0.0511        | 8.0   | 2544 | 0.0337          | 0.9310   |
-| 0.0488        | 9.0   | 2862 | 0.0325          | 0.9319   |
-| 0.0476        | 10.0  | 3180 | 0.0323          | 0.9319   |
 ### Framework versions

     metrics:
     - name: Accuracy
       type: accuracy
+      value: 0.9448387096774193
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.2061
+- Accuracy: 0.9448
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.7308        | 1.0   | 318  | 1.1633          | 0.7394   |
+| 0.8985        | 2.0   | 636  | 0.5726          | 0.8635   |
+| 0.4735        | 3.0   | 954  | 0.3350          | 0.9187   |
+| 0.298         | 4.0   | 1272 | 0.2562          | 0.9361   |
+| 0.2313        | 5.0   | 1590 | 0.2304          | 0.9413   |
+| 0.2043        | 6.0   | 1908 | 0.2190          | 0.9432   |
+| 0.1904        | 7.0   | 2226 | 0.2130          | 0.9445   |
+| 0.1829        | 8.0   | 2544 | 0.2091          | 0.9442   |
+| 0.1782        | 9.0   | 2862 | 0.2066          | 0.9455   |
+| 0.1762        | 10.0  | 3180 | 0.2061          | 0.9448   |
 ### Framework versions