End of training

README.md

@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3450
-- Accuracy: 0.9206
-- Precision: 0.9242
-- Recall: 0.9206
-- F1: 0.9202
+- Loss: 0.1266
+- Accuracy: 0.9683
+- Precision: 0.9718
+- Recall: 0.9683
+- F1: 0.9683
 
 ## Model description
 
@@ -43,7 +43,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 3e-05
+- learning_rate: 5e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
@@ -55,11 +55,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
-| 1.2965        | 1.0   | 16   | 1.0060          | 0.6190   | 0.7989    | 0.6190 | 0.5413 |
-| 0.8967        | 2.0   | 32   | 0.7731          | 0.8571   | 0.9005    | 0.8571 | 0.8556 |
-| 0.6978        | 3.0   | 48   | 0.5247          | 0.9365   | 0.9382    | 0.9365 | 0.9364 |
-| 0.4319        | 4.0   | 64   | 0.3859          | 0.9365   | 0.9382    | 0.9365 | 0.9364 |
-| 0.3069        | 5.0   | 80   | 0.3450          | 0.9206   | 0.9242    | 0.9206 | 0.9202 |
+| 1.1987        | 1.0   | 16   | 0.7846          | 0.9206   | 0.9253    | 0.9206 | 0.9207 |
+| 0.5283        | 2.0   | 32   | 0.3242          | 0.9841   | 0.9851    | 0.9841 | 0.9841 |
+| 0.3106        | 3.0   | 48   | 0.1674          | 0.9683   | 0.9718    | 0.9683 | 0.9683 |
+| 0.0971        | 4.0   | 64   | 0.1073          | 0.9683   | 0.9718    | 0.9683 | 0.9683 |
+| 0.047         | 5.0   | 80   | 0.1266          | 0.9683   | 0.9718    | 0.9683 | 0.9683 |
 
 
 ### Framework versions

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