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: 0.9275
+      value: 0.9255
     - name: F1
       type: f1
-      value: 0.9273308996920793
+      value: 0.9255503643924508
 ---
 
 <!-- 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: 0.2015
-- Accuracy: 0.9275
-- F1: 0.9273
+- Loss: 0.2150
+- Accuracy: 0.9255
+- F1: 0.9256
 
 ## Model description
 
@@ -68,13 +69,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8115        | 1.0   | 250  | 0.2879          | 0.9105   | 0.9080 |
-| 0.238         | 2.0   | 500  | 0.2015          | 0.9275   | 0.9273 |
+| 0.8042        | 1.0   | 250  | 0.3079          | 0.9075   | 0.9068 |
+| 0.2448        | 2.0   | 500  | 0.2150          | 0.9255   | 0.9256 |
 
 
 ### Framework versions
 
-- Transformers 4.29.1
-- Pytorch 2.0.0+cu118
-- Datasets 2.12.0
-- Tokenizers 0.13.3
+- Transformers 4.41.0
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

runs/May23_04-18-03_74de3b245202/events.out.tfevents.1716437885.74de3b245202.1639.0

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