Fine-tuning Complete

README.md

@@ -5,9 +5,28 @@ tags:
 - generated_from_trainer
 datasets:
 - emotion
+metrics:
+- accuracy
+- f1
 model-index:
 - name: distilbert-base-uncased-finetuned-emotion
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: emotion
+      type: emotion
+      config: split
+      split: validation
+      args: split
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9275
+    - name: F1
+      type: f1
+      value: 0.9272809917120055
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +35,10 @@ should probably proofread and complete it, then remove this comment. -->
 # distilbert-base-uncased-finetuned-emotion
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2168
+- Accuracy: 0.9275
+- F1: 0.9273
 
 ## Model description
 
@@ -42,6 +65,14 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 2
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.5564        | 1.0   | 250  | 0.3202          | 0.9095   | 0.9088 |
+| 0.2291        | 2.0   | 500  | 0.2168          | 0.9275   | 0.9273 |
+
+
 ### Framework versions
 
 - Transformers 4.34.1