Training complete

README.md

@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1733
-- Precision: 0.7598
-- Recall: 0.8054
-- F1: 0.7819
-- Accuracy: 0.9670
+- Loss: 0.1741
+- Precision: 0.7713
+- Recall: 0.8081
+- F1: 0.7893
+- Accuracy: 0.9675
 
 ## Model description
 
@@ -55,16 +55,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.1049        | 1.0   | 1041 | 0.1568          | 0.7038    | 0.7383 | 0.7206 | 0.9582   |
-| 0.069         | 2.0   | 2082 | 0.1487          | 0.6969    | 0.7714 | 0.7322 | 0.9623   |
-| 0.0426        | 3.0   | 3123 | 0.1424          | 0.7563    | 0.8008 | 0.7779 | 0.9676   |
-| 0.0271        | 4.0   | 4164 | 0.1594          | 0.7604    | 0.7948 | 0.7772 | 0.9666   |
-| 0.022         | 5.0   | 5205 | 0.1733          | 0.7598    | 0.8054 | 0.7819 | 0.9670   |
+| 0.1035        | 1.0   | 1041 | 0.1460          | 0.7285    | 0.7590 | 0.7434 | 0.9614   |
+| 0.0684        | 2.0   | 2082 | 0.1438          | 0.7017    | 0.7767 | 0.7373 | 0.9631   |
+| 0.0423        | 3.0   | 3123 | 0.1504          | 0.7591    | 0.7978 | 0.7780 | 0.9670   |
+| 0.0278        | 4.0   | 4164 | 0.1606          | 0.7683    | 0.8008 | 0.7842 | 0.9670   |
+| 0.0207        | 5.0   | 5205 | 0.1741          | 0.7713    | 0.8081 | 0.7893 | 0.9675   |
 
 
 ### Framework versions
 
 - Transformers 4.40.1
-- Pytorch 2.2.1+cu121
-- Datasets 2.19.0
+- Pytorch 2.0.1+cu117
+- Datasets 2.18.0
 - Tokenizers 0.19.1