End of training

README.md

@@ -5,9 +5,30 @@ tags:
 - generated_from_trainer
 datasets:
 - clinc_oos
+metrics:
+- accuracy
+- f1
 model-index:
 - name: distilbert-base-uncased-finetuned-clinc_oos
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: clinc_oos
+      type: clinc_oos
+      config: plus
+      split: validation
+      args: plus
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value:
+        accuracy: 0.9248387096774193
+    - name: F1
+      type: f1
+      value:
+        f1: 0.924017622321749
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +37,10 @@ should probably proofread and complete it, then remove this comment. -->
 # distilbert-base-uncased-finetuned-clinc_oos
 
 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: 0.6012
+- Accuracy: {'accuracy': 0.9248387096774193}
+- F1: {'f1': 0.924017622321749}
 
 ## Model description
 
@@ -42,6 +67,15 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 3
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy                         | F1                         |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:--------------------------:|
+| 4.3563        | 1.0   | 954  | 2.0254          | {'accuracy': 0.8274193548387097} | {'f1': 0.8157244857086648} |
+| 1.5387        | 2.0   | 1908 | 0.8120          | {'accuracy': 0.9129032258064517} | {'f1': 0.9118433401777696} |
+| 0.6711        | 3.0   | 2862 | 0.6012          | {'accuracy': 0.9248387096774193} | {'f1': 0.924017622321749}  |
+
+
 ### Framework versions
 
 - Transformers 4.33.1

pytorch_model.bin

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