End of training

README.md

@@ -17,15 +17,15 @@ 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: 0.0936
-- Accuracy: 0.9798
-- F1 Macro: 0.9765
-- Accuracy Balanced: 0.9751
-- F1 Micro: 0.9798
-- Precision Macro: 0.9780
-- Recall Macro: 0.9751
-- Precision Micro: 0.9798
-- Recall Micro: 0.9798
+- Loss: 0.0807
+- Accuracy: 0.975
+- F1 Macro: 0.9710
+- Accuracy Balanced: 0.9715
+- F1 Micro: 0.975
+- Precision Macro: 0.9705
+- Recall Macro: 0.9715
+- Precision Micro: 0.975
+- Recall Micro: 0.975
 
 ## Model description
 
@@ -59,16 +59,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Accuracy Balanced | F1 Micro | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
-| No log        | 1.0   | 123  | 0.1778          | 0.9609   | 0.9543   | 0.9510            | 0.9609   | 0.9577          | 0.9510       | 0.9609          | 0.9609       |
-| No log        | 2.0   | 246  | 0.1614          | 0.9680   | 0.9626   | 0.9593            | 0.9680   | 0.9661          | 0.9593       | 0.9680          | 0.9680       |
-| No log        | 3.0   | 369  | 0.1598          | 0.9680   | 0.9626   | 0.9593            | 0.9680   | 0.9661          | 0.9593       | 0.9680          | 0.9680       |
-| No log        | 4.0   | 492  | 0.1191          | 0.9703   | 0.9653   | 0.9610            | 0.9703   | 0.9699          | 0.9610       | 0.9703          | 0.9703       |
-| 0.1357        | 5.0   | 615  | 0.1400          | 0.9727   | 0.9681   | 0.9638            | 0.9727   | 0.9727          | 0.9638       | 0.9727          | 0.9727       |
+| No log        | 1.0   | 123  | 0.1057          | 0.9726   | 0.9675   | 0.9583            | 0.9726   | 0.9783          | 0.9583       | 0.9726          | 0.9726       |
+| No log        | 2.0   | 246  | 0.1102          | 0.9726   | 0.9683   | 0.9697            | 0.9726   | 0.9669          | 0.9697       | 0.9726          | 0.9726       |
+| No log        | 3.0   | 369  | 0.0894          | 0.9798   | 0.9763   | 0.9729            | 0.9798   | 0.9800          | 0.9729       | 0.9798          | 0.9798       |
+| No log        | 4.0   | 492  | 0.1098          | 0.9762   | 0.9723   | 0.9723            | 0.9762   | 0.9723          | 0.9723       | 0.9762          | 0.9762       |
+| 0.1374        | 5.0   | 615  | 0.1026          | 0.9798   | 0.9763   | 0.9729            | 0.9798   | 0.9800          | 0.9729       | 0.9798          | 0.9798       |
 
 
 ### Framework versions
 
 - Transformers 4.36.2
-- Pytorch 2.1.0+cu121
+- Pytorch 2.5.0+cu121
 - Datasets 2.6.0
-- Tokenizers 0.15.1
+- Tokenizers 0.15.2

model.safetensors

@@ -1,3 +1,3 @@
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 size 737719272