End of training

README.md

@@ -18,10 +18,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0504
+- Loss: 0.0035
 - F1: 0.0
 - Roc Auc: 0.5
-- Accuracy: 0.96
+- Accuracy: 0.9824
 
 ## Model description
 
@@ -52,21 +52,21 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | F1  | Roc Auc | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---:|:-------:|:--------:|
-| No log        | 1.0   | 35   | 0.3812          | 0.0 | 0.5     | 0.96     |
-| No log        | 2.0   | 70   | 0.2404          | 0.0 | 0.5     | 0.96     |
-| No log        | 3.0   | 105  | 0.1566          | 0.0 | 0.5     | 0.96     |
-| No log        | 4.0   | 140  | 0.1087          | 0.0 | 0.5     | 0.96     |
-| No log        | 5.0   | 175  | 0.0822          | 0.0 | 0.5     | 0.96     |
-| No log        | 6.0   | 210  | 0.0674          | 0.0 | 0.5     | 0.96     |
-| No log        | 7.0   | 245  | 0.0588          | 0.0 | 0.5     | 0.96     |
-| No log        | 8.0   | 280  | 0.0539          | 0.0 | 0.5     | 0.96     |
-| No log        | 9.0   | 315  | 0.0512          | 0.0 | 0.5     | 0.96     |
-| No log        | 10.0  | 350  | 0.0504          | 0.0 | 0.5     | 0.96     |
+| No log        | 1.0   | 222  | 0.0251          | 0.0 | 0.5     | 0.9824   |
+| No log        | 2.0   | 444  | 0.0088          | 0.0 | 0.5     | 0.9824   |
+| 0.1019        | 3.0   | 666  | 0.0068          | 0.0 | 0.5     | 0.9824   |
+| 0.1019        | 4.0   | 888  | 0.0056          | 0.0 | 0.5     | 0.9824   |
+| 0.0148        | 5.0   | 1110 | 0.0051          | 0.0 | 0.5     | 0.9824   |
+| 0.0148        | 6.0   | 1332 | 0.0042          | 0.0 | 0.5     | 0.9824   |
+| 0.0119        | 7.0   | 1554 | 0.0040          | 0.0 | 0.5     | 0.9824   |
+| 0.0119        | 8.0   | 1776 | 0.0036          | 0.0 | 0.5     | 0.9824   |
+| 0.0119        | 9.0   | 1998 | 0.0035          | 0.0 | 0.5     | 0.9824   |
+| 0.0101        | 10.0  | 2220 | 0.0035          | 0.0 | 0.5     | 0.9824   |
 
 
 ### Framework versions
 
 - Transformers 4.35.2
-- Pytorch 2.1.0+cu118
-- Datasets 2.15.0
-- Tokenizers 0.15.0
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1