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 [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0681
-- Precision: 0.6874
-- Recall: 0.7731
-- F1: 0.7278
-- Accuracy: 0.9771
+- Loss: 0.0606
+- Precision: 0.6730
+- Recall: 0.7899
+- F1: 0.7268
+- Accuracy: 0.9783
 
 ## Model description
 
@@ -55,16 +55,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 55   | 0.0748          | 0.5784    | 0.6457 | 0.6102 | 0.9699   |
-| No log        | 2.0   | 110  | 0.0709          | 0.6174    | 0.7773 | 0.6882 | 0.9750   |
-| No log        | 3.0   | 165  | 0.0670          | 0.6460    | 0.7899 | 0.7108 | 0.9758   |
-| No log        | 4.0   | 220  | 0.0628          | 0.6966    | 0.7717 | 0.7322 | 0.9775   |
-| No log        | 5.0   | 275  | 0.0681          | 0.6874    | 0.7731 | 0.7278 | 0.9771   |
+| No log        | 1.0   | 55   | 0.0744          | 0.5840    | 0.6527 | 0.6164 | 0.9703   |
+| No log        | 2.0   | 110  | 0.0639          | 0.6332    | 0.7689 | 0.6945 | 0.9764   |
+| No log        | 3.0   | 165  | 0.0585          | 0.6424    | 0.7801 | 0.7046 | 0.9766   |
+| No log        | 4.0   | 220  | 0.0581          | 0.6754    | 0.7955 | 0.7305 | 0.9785   |
+| No log        | 5.0   | 275  | 0.0606          | 0.6730    | 0.7899 | 0.7268 | 0.9783   |
 
 
 ### Framework versions
 
-- Transformers 4.33.0
+- Transformers 4.33.2
 - Pytorch 2.0.1+cu118
-- Datasets 2.14.4
+- Datasets 2.14.5
 - Tokenizers 0.13.3