Training completed!

README.md

@@ -1,5 +1,6 @@
 ---
 license: apache-2.0
+base_model: distilbert-base-uncased
 tags:
 - generated_from_trainer
 datasets:
@@ -16,16 +17,16 @@ model-index:
     dataset:
       name: emotion
       type: emotion
-      config: default
-      split: train
-      args: default
+      config: split
+      split: validation
+      args: split
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.923
+      value: 0.925
     - name: F1
       type: f1
-      value: 0.9226309564543956
+      value: 0.9248748420162367
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,9 +36,9 @@ 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 emotion dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2256
-- Accuracy: 0.923
-- F1: 0.9226
+- Loss: 0.2202
+- Accuracy: 0.925
+- F1: 0.9249
 
 ## Model description
 
@@ -68,13 +69,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.807         | 1.0   | 250  | 0.3202          | 0.8995   | 0.8968 |
-| 0.2491        | 2.0   | 500  | 0.2256          | 0.923    | 0.9226 |
+| 0.8552        | 1.0   | 250  | 0.3378          | 0.903    | 0.9018 |
+| 0.2598        | 2.0   | 500  | 0.2202          | 0.925    | 0.9249 |
 
 
 ### Framework versions
 
-- Transformers 4.23.1
-- Pytorch 1.12.1+cu113
-- Datasets 2.6.1
-- Tokenizers 0.13.1
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.1

runs/Feb13_20-45-25_15f672b7130c/events.out.tfevents.1707857126.15f672b7130c.17576.0

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