Training complete

README.md

@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2347
-- Precision: 0.4874
-- Recall: 0.6780
-- F1: 0.5671
-- Accuracy: 0.9425
+- Loss: 0.2334
+- Precision: 0.5768
+- Recall: 0.6721
+- F1: 0.6208
+- Accuracy: 0.9219
 
 ## Model description
 
@@ -48,7 +48,7 @@ The following hyperparameters were used during training:
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
-- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - num_epochs: 3
 
@@ -56,13 +56,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 249  | 0.2283          | 0.4375    | 0.6068 | 0.5084 | 0.9391   |
-| No log        | 2.0   | 498  | 0.2253          | 0.4571    | 0.6760 | 0.5454 | 0.9387   |
-| 0.2024        | 3.0   | 747  | 0.2347          | 0.4874    | 0.6780 | 0.5671 | 0.9425   |
+| No log        | 1.0   | 125  | 0.2637          | 0.5299    | 0.6395 | 0.5796 | 0.9170   |
+| No log        | 2.0   | 250  | 0.2318          | 0.5752    | 0.6674 | 0.6179 | 0.9231   |
+| No log        | 3.0   | 375  | 0.2334          | 0.5768    | 0.6721 | 0.6208 | 0.9219   |
 
 
 ### Framework versions
 
-- Transformers 4.46.2
-- Pytorch 2.5.0+cu121
-- Tokenizers 0.20.3
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0