Training completed!

README.md

@@ -1,5 +1,6 @@
 ---
 license: apache-2.0
+base_model: distilbert-base-uncased
 tags:
 - generated_from_trainer
 datasets:
@@ -22,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.938
+      value: 0.927
     - name: F1
       type: f1
-      value: 0.9382222634823464
+      value: 0.926984518712486
 ---
 
 <!-- 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: 0.1611
-- Accuracy: 0.938
-- F1: 0.9382
+- Loss: 0.2213
+- Accuracy: 0.927
+- F1: 0.9270
 
 ## Model description
 
@@ -68,13 +69,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.2043        | 1.0   | 250  | 0.1804          | 0.9275   | 0.9270 |
-| 0.1334        | 2.0   | 500  | 0.1611          | 0.938    | 0.9382 |
+| 0.845         | 1.0   | 250  | 0.3299          | 0.9025   | 0.9003 |
+| 0.2539        | 2.0   | 500  | 0.2213          | 0.927    | 0.9270 |
 
 
 ### Framework versions
 
-- Transformers 4.26.0
-- Pytorch 1.13.1+cu116
-- Datasets 2.9.0
-- Tokenizers 0.13.2
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.1