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: 0.0091
-- Precision: 0.7601
-- Recall: 0.7219
-- F1: 0.7405
-- Accuracy: 0.9976
+- Loss: 0.0098
+- Precision: 0.7014
+- Recall: 0.6918
+- F1: 0.6966
+- Accuracy: 0.9975
 
 ## Model description
 
@@ -55,14 +55,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0461        | 1.0   | 635  | 0.0107          | 0.7529    | 0.5858 | 0.6589 | 0.9972   |
-| 0.0098        | 2.0   | 1270 | 0.0087          | 0.7176    | 0.7219 | 0.7198 | 0.9974   |
-| 0.0068        | 3.0   | 1905 | 0.0091          | 0.7601    | 0.7219 | 0.7405 | 0.9976   |
+| 0.0445        | 1.0   | 708  | 0.0106          | 0.6792    | 0.4932 | 0.5714 | 0.9971   |
+| 0.0098        | 2.0   | 1416 | 0.0095          | 0.6875    | 0.6781 | 0.6828 | 0.9974   |
+| 0.0035        | 3.0   | 2124 | 0.0098          | 0.7014    | 0.6918 | 0.6966 | 0.9975   |
 
 
 ### 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