Model save

README.md

@@ -18,14 +18,14 @@ 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: 0.1973
-- F1 Macro: 0.9515
-- F1: 0.9667
-- F1 Neg: 0.9362
-- Acc: 0.9563
-- Prec: 0.9639
-- Recall: 0.9695
-- Mcc: 0.9030
+- Loss: 0.1598
+- F1 Macro: 0.9639
+- F1: 0.9753
+- F1 Neg: 0.9526
+- Acc: 0.9675
+- Prec: 0.9716
+- Recall: 0.9790
+- Mcc: 0.9279
 
 ## Model description
 
@@ -56,16 +56,11 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1     | F1 Neg | Acc    | Prec   | Recall | Mcc    |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
-| No log        | 1.0   | 400  | 0.2396          | 0.9196   | 0.9485 | 0.8906 | 0.93   | 0.9149 | 0.9847 | 0.8452 |
-| 0.2339        | 2.0   | 800  | 0.1973          | 0.9515   | 0.9667 | 0.9362 | 0.9563 | 0.9639 | 0.9695 | 0.9030 |
-| 0.1245        | 3.0   | 1200 | 0.2447          | 0.9485   | 0.9649 | 0.9321 | 0.9537 | 0.9586 | 0.9714 | 0.8972 |
 
 
 ### Framework versions
 
-- Transformers 4.37.2
-- Pytorch 2.2.0+cu121
-- Datasets 2.16.1
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
 - Tokenizers 0.15.2