Training completed

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.926
+      value: 0.924
     - name: F1
       type: f1
-      value: 0.925964511235661
+      value: 0.9238842970134016
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -36,9 +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: 0.2134
-- Accuracy: 0.926
-- F1: 0.9260
+- Loss: 0.2208
+- Accuracy: 0.924
+- F1: 0.9239
 
 ## Model description
 
@@ -69,13 +69,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| No log        | 1.0   | 250  | 0.3089          | 0.9145   | 0.9141 |
-| 0.5193        | 2.0   | 500  | 0.2134          | 0.926    | 0.9260 |
+| No log        | 1.0   | 250  | 0.3242          | 0.9045   | 0.9036 |
+| 0.5423        | 2.0   | 500  | 0.2208          | 0.924    | 0.9239 |
 
 
 ### Framework versions
 
-- Transformers 4.34.1
+- Transformers 4.35.2
 - Pytorch 2.1.0+cu118
-- Datasets 2.14.6
-- Tokenizers 0.14.1
+- Datasets 2.15.0
+- Tokenizers 0.15.0

runs/Nov21_17-46-01_d5849fb3fe67/events.out.tfevents.1700588764.d5849fb3fe67.136.0

@@ -1,3 +1,3 @@
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+size 5632