Training completed! - 3 epochs

README.md

@@ -5,9 +5,24 @@ tags:
 - generated_from_trainer
 datasets:
 - emotion
+metrics:
+- accuracy
 model-index:
 - name: distilbert-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: 0.9385
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +31,9 @@ should probably proofread and complete it, then remove this comment. -->
 # distilbert-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: 0.1333
+- Accuracy: 0.9385
 
 ## Model description
 
@@ -40,18 +58,20 @@ 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: 1
+- num_epochs: 3
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 250  | 0.2190          | 0.92     |
+| No log        | 1.0   | 250  | 0.1954          | 0.926    |
+| 0.3494        | 2.0   | 500  | 0.1472          | 0.937    |
+| 0.3494        | 3.0   | 750  | 0.1333          | 0.9385   |
 
 
 ### Framework versions
 
 - Transformers 4.34.1
-- Pytorch 2.0.1+cpu
+- Pytorch 2.1.0+cpu
 - Datasets 2.14.5
 - Tokenizers 0.14.1