Training completed

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.926
+      value: 0.923
     - name: F1
       type: f1
-      value: 0.9261772417120997
+      value: 0.92304659943046
 ---
 
 <!-- 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: 0.2141
-- Accuracy: 0.926
-- F1: 0.9262
+- Loss: 0.2302
+- Accuracy: 0.923
+- F1: 0.9230
 
 ## Model description
 
@@ -69,8 +69,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| No log        | 1.0   | 250  | 0.3080          | 0.9055   | 0.9051 |
-| 0.5322        | 2.0   | 500  | 0.2141          | 0.926    | 0.9262 |
+| No log        | 1.0   | 250  | 0.3194          | 0.911    | 0.9105 |
+| 0.5519        | 2.0   | 500  | 0.2302          | 0.923    | 0.9230 |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
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 size 267844872

runs/Jan04_04-46-34_95cc724f5756/events.out.tfevents.1704347759.95cc724f5756.263.1

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