update model card README.md

README.md

@@ -2,12 +2,30 @@
 license: apache-2.0
 tags:
 - generated_from_trainer
+datasets:
+- tweets_hate_speech_detection
 metrics:
 - accuracy
 - f1
 model-index:
 - name: Hate-Speech-Detection-mpnet-basev2
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: tweets_hate_speech_detection
+      type: tweets_hate_speech_detection
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9749726263100266
+    - name: F1
+      type: f1
+      value: 0.8029556650246304
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,11 +33,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # Hate-Speech-Detection-mpnet-basev2
 
-This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the None dataset.
+This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the tweets_hate_speech_detection dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4546
-- Accuracy: 0.9320
-- F1: 0.9317
+- Loss: 0.0849
+- Accuracy: 0.9750
+- F1: 0.8030
 
 ## Model description
 
@@ -48,23 +66,15 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| No log        | 1.0   | 225  | 0.2916          | 0.8952   | 0.9027 |
-| No log        | 2.0   | 450  | 0.2543          | 0.9153   | 0.9156 |
-| 0.2816        | 3.0   | 675  | 0.2853          | 0.9164   | 0.9158 |
-| 0.2816        | 4.0   | 900  | 0.3623          | 0.9197   | 0.9221 |
-| 0.0831        | 5.0   | 1125 | 0.4164          | 0.9186   | 0.9207 |
-| 0.0831        | 6.0   | 1350 | 0.4079          | 0.9208   | 0.9198 |
-| 0.0232        | 7.0   | 1575 | 0.4187          | 0.9275   | 0.9267 |
-| 0.0232        | 8.0   | 1800 | 0.4831          | 0.9231   | 0.9246 |
-| 0.0089        | 9.0   | 2025 | 0.4570          | 0.9298   | 0.9305 |
-| 0.0089        | 10.0  | 2250 | 0.4546          | 0.9320   | 0.9317 |
-| 0.0089        | 11.0  | 2475 | 0.5022          | 0.9264   | 0.9278 |
-| 0.0051        | 12.0  | 2700 | 0.5734          | 0.9208   | 0.9232 |
-| 0.0051        | 13.0  | 2925 | 0.5780          | 0.9186   | 0.9211 |
-| 0.002         | 14.0  | 3150 | 0.5049          | 0.9287   | 0.9295 |
-| 0.002         | 15.0  | 3375 | 0.5444          | 0.9231   | 0.9249 |
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
+| 0.1144        | 1.0   | 1599  | 0.0955          | 0.9693   | 0.7337 |
+| 0.072         | 2.0   | 3198  | 0.0849          | 0.9750   | 0.8030 |
+| 0.0458        | 3.0   | 4797  | 0.0841          | 0.9764   | 0.8011 |
+| 0.0156        | 4.0   | 6396  | 0.1829          | 0.9689   | 0.7762 |
+| 0.012         | 5.0   | 7995  | 0.1904          | 0.9745   | 0.7758 |
+| 0.0157        | 6.0   | 9594  | 0.1622          | 0.9758   | 0.7914 |
+| 0.0068        | 7.0   | 11193 | 0.1741          | 0.9736   | 0.8005 |
 
 
 ### Framework versions