End of training

README.md

@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [austin/Austin-MeDeBERTa](https://huggingface.co/austin/Austin-MeDeBERTa) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0102
-- Precision: 0.7108
-- Recall: 0.6507
-- F1: 0.6794
-- Accuracy: 0.9972
+- Loss: 0.0106
+- Precision: 0.7077
+- Recall: 0.7188
+- F1: 0.7132
+- Accuracy: 0.9971
 
 ## Model description
 
@@ -55,14 +55,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0447        | 1.0   | 635  | 0.0125          | 0.5988    | 0.5549 | 0.5760 | 0.9964   |
-| 0.0106        | 2.0   | 1270 | 0.0097          | 0.6728    | 0.6197 | 0.6452 | 0.9970   |
-| 0.0067        | 3.0   | 1905 | 0.0102          | 0.7108    | 0.6507 | 0.6794 | 0.9972   |
+| 0.0405        | 1.0   | 708  | 0.0124          | 0.6111    | 0.6302 | 0.6205 | 0.9964   |
+| 0.0096        | 2.0   | 1416 | 0.0100          | 0.8311    | 0.6406 | 0.7235 | 0.9973   |
+| 0.0037        | 3.0   | 2124 | 0.0106          | 0.7077    | 0.7188 | 0.7132 | 0.9971   |
 
 
 ### Framework versions
 
-- Transformers 4.37.0.dev0
+- Transformers 4.39.0.dev0
 - Pytorch 2.1.0+cu121
-- Datasets 2.16.1
-- Tokenizers 0.15.0
+- Datasets 2.17.1
+- Tokenizers 0.15.2