LovenOO
/

BERT_with_preprocessing_grid_search

@@ -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: 0.8335
-- Precision: 0.8310
-- Recall: 0.8213
-- F1: 0.8256
-- Accuracy: 0.8640
 ## Model description
@@ -43,7 +43,7 @@ More information needed
 ### Training hyperparameters
 The following hyperparameters were used during training:
-- learning_rate: 3e-05
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
@@ -55,16 +55,16 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 255  | 0.6597          | 0.7225    | 0.7990 | 0.7429 | 0.7968   |
-| 0.8033        | 2.0   | 510  | 0.5609          | 0.8155    | 0.8378 | 0.8247 | 0.8596   |
-| 0.8033        | 3.0   | 765  | 0.5589          | 0.8119    | 0.8388 | 0.8231 | 0.8591   |
-| 0.2454        | 4.0   | 1020 | 0.6598          | 0.8314    | 0.8273 | 0.8279 | 0.8625   |
-| 0.2454        | 5.0   | 1275 | 0.6541          | 0.8103    | 0.8393 | 0.8229 | 0.8625   |
-| 0.1332        | 6.0   | 1530 | 0.8259          | 0.8424    | 0.8213 | 0.8304 | 0.8665   |
-| 0.1332        | 7.0   | 1785 | 0.7644          | 0.8298    | 0.8335 | 0.8312 | 0.8650   |
-| 0.0907        | 8.0   | 2040 | 0.7939          | 0.8298    | 0.8255 | 0.8274 | 0.8660   |
-| 0.0907        | 9.0   | 2295 | 0.8244          | 0.8310    | 0.8207 | 0.8255 | 0.8655   |
-| 0.061         | 10.0  | 2550 | 0.8335          | 0.8310    | 0.8213 | 0.8256 | 0.8640   |
 ### Framework versions

 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: 0.7918
+- Precision: 0.8374
+- Recall: 0.8246
+- F1: 0.8306
+- Accuracy: 0.8645
 ## Model description
 ### Training hyperparameters
 The following hyperparameters were used during training:
+- learning_rate: 2e-05
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 255  | 0.7382          | 0.7058    | 0.7789 | 0.7260 | 0.7894   |
+| 0.907         | 2.0   | 510  | 0.5794          | 0.7838    | 0.8189 | 0.7976 | 0.8444   |
+| 0.907         | 3.0   | 765  | 0.5382          | 0.8084    | 0.8375 | 0.8200 | 0.8547   |
+| 0.2877        | 4.0   | 1020 | 0.5942          | 0.8301    | 0.8319 | 0.8301 | 0.8670   |
+| 0.2877        | 5.0   | 1275 | 0.6349          | 0.8198    | 0.8384 | 0.8280 | 0.8655   |
+| 0.1513        | 6.0   | 1530 | 0.7735          | 0.8384    | 0.8144 | 0.8250 | 0.8635   |
+| 0.1513        | 7.0   | 1785 | 0.7221          | 0.8456    | 0.8333 | 0.8385 | 0.8704   |
+| 0.1059        | 8.0   | 2040 | 0.7615          | 0.8390    | 0.8312 | 0.8349 | 0.8684   |
+| 0.1059        | 9.0   | 2295 | 0.7841          | 0.8362    | 0.8253 | 0.8306 | 0.8684   |
+| 0.0811        | 10.0  | 2550 | 0.7918          | 0.8374    | 0.8246 | 0.8306 | 0.8645   |
 ### Framework versions