End of training

README.md

@@ -20,7 +20,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0009
+- Loss: 0.0012
 - Accuracy: {'accuracy': 1.0}
 - Precision: {'precision': 1.0}
 - Recall: {'recall': 1.0}
@@ -55,13 +55,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy          | Precision          | Recall          | F1          |
 |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:------------------:|:---------------:|:-----------:|
-| No log        | 1.0   | 160  | 0.0015          | {'accuracy': 1.0} | {'precision': 1.0} | {'recall': 1.0} | {'f1': 1.0} |
-| No log        | 2.0   | 320  | 0.0009          | {'accuracy': 1.0} | {'precision': 1.0} | {'recall': 1.0} | {'f1': 1.0} |
+| No log        | 1.0   | 160  | 0.0021          | {'accuracy': 1.0} | {'precision': 1.0} | {'recall': 1.0} | {'f1': 1.0} |
+| No log        | 2.0   | 320  | 0.0012          | {'accuracy': 1.0} | {'precision': 1.0} | {'recall': 1.0} | {'f1': 1.0} |
 
 
 ### Framework versions
 
 - Transformers 4.40.1
 - Pytorch 2.2.1+cu121
-- Datasets 2.19.0
+- Datasets 2.19.1
 - Tokenizers 0.19.1