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: 0.8911
-- Precision: 0.8371
-- Recall: 0.8239
-- F1: 0.8296
-- Accuracy: 0.8665
 ## Model description
@@ -43,7 +43,7 @@ More information needed
 ### Training hyperparameters
 The following hyperparameters were used during training:
-- learning_rate: 5e-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  | 0.6320          | 0.7746    | 0.8197 | 0.7918 | 0.8360   |
-| 0.7073        | 2.0   | 510  | 0.6156          | 0.7967    | 0.8232 | 0.8055 | 0.8473   |
-| 0.7073        | 3.0   | 765  | 0.6028          | 0.8104    | 0.8381 | 0.8201 | 0.8552   |
-| 0.2389        | 4.0   | 1020 | 0.6896          | 0.8296    | 0.8296 | 0.8290 | 0.8655   |
-| 0.2389        | 5.0   | 1275 | 0.7462          | 0.8279    | 0.8353 | 0.8310 | 0.8694   |
-| 0.1264        | 6.0   | 1530 | 0.9275          | 0.8488    | 0.8112 | 0.8271 | 0.8684   |
-| 0.1264        | 7.0   | 1785 | 0.8244          | 0.8393    | 0.8313 | 0.8347 | 0.8729   |
-| 0.0851        | 8.0   | 2040 | 0.8776          | 0.8281    | 0.8226 | 0.8249 | 0.8655   |
-| 0.0851        | 9.0   | 2295 | 0.8838          | 0.8440    | 0.8278 | 0.8346 | 0.8675   |
-| 0.0546        | 10.0  | 2550 | 0.8911          | 0.8371    | 0.8239 | 0.8296 | 0.8665   |
 ### 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: 0.8335
+- Precision: 0.8310
+- Recall: 0.8213
+- F1: 0.8256
+- Accuracy: 0.8640
 ## Model description
 ### Training hyperparameters
 The following hyperparameters were used during training:
+- learning_rate: 3e-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  | 0.6597          | 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