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: 0.0090
-- Precision: 0.7446
-- Recall: 0.7718
-- F1: 0.7580
-- Accuracy: 0.9975
+- Loss: 0.0102
+- Precision: 0.6842
+- Recall: 0.7772
+- F1: 0.7277
+- Accuracy: 0.9969
 
 ## Model description
 
@@ -55,14 +55,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0403        | 1.0   | 635  | 0.0103          | 0.6230    | 0.6563 | 0.6392 | 0.9968   |
-| 0.0097        | 2.0   | 1270 | 0.0082          | 0.7291    | 0.7352 | 0.7321 | 0.9974   |
-| 0.0056        | 3.0   | 1905 | 0.0090          | 0.7446    | 0.7718 | 0.7580 | 0.9975   |
+| 0.0362        | 1.0   | 708  | 0.0109          | 0.6517    | 0.6304 | 0.6409 | 0.9963   |
+| 0.0087        | 2.0   | 1416 | 0.0092          | 0.6618    | 0.7337 | 0.6959 | 0.9968   |
+| 0.0029        | 3.0   | 2124 | 0.0102          | 0.6842    | 0.7772 | 0.7277 | 0.9969   |
 
 
 ### 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