LovenOO
/

BERT_without_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: 0.6705
-- Precision: 0.8452
-- Recall: 0.8581
-- F1: 0.8510
-- Accuracy: 0.8818
 ## 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   | 257  | 0.5962          | 0.7414    | 0.8132 | 0.7626 | 0.8268   |
-| 0.7597        | 2.0   | 514  | 0.5120          | 0.8170    | 0.8507 | 0.8292 | 0.8652   |
-| 0.7597        | 3.0   | 771  | 0.4818          | 0.7975    | 0.8565 | 0.8202 | 0.8652   |
-| 0.2391        | 4.0   | 1028 | 0.5223          | 0.8220    | 0.8613 | 0.8377 | 0.8652   |
-| 0.2391        | 5.0   | 1285 | 0.5516          | 0.8172    | 0.8599 | 0.8347 | 0.8706   |
-| 0.1316        | 6.0   | 1542 | 0.5747          | 0.8139    | 0.8593 | 0.8333 | 0.8710   |
-| 0.1316        | 7.0   | 1799 | 0.6290          | 0.8332    | 0.8483 | 0.8386 | 0.8701   |
-| 0.0773        | 8.0   | 2056 | 0.6089          | 0.8312    | 0.8620 | 0.8450 | 0.8764   |
-| 0.0773        | 9.0   | 2313 | 0.6633          | 0.8384    | 0.8532 | 0.8448 | 0.8774   |
-| 0.0633        | 10.0  | 2570 | 0.6705          | 0.8452    | 0.8581 | 0.8510 | 0.8818   |
 ### 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: 0.6213
+- Precision: 0.8399
+- Recall: 0.8622
+- F1: 0.8498
+- Accuracy: 0.8798
 ## 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   | 257  | 0.6305          | 0.7254    | 0.8018 | 0.7512 | 0.8180   |
+| 0.8689        | 2.0   | 514  | 0.4877          | 0.8120    | 0.8500 | 0.8245 | 0.8667   |
+| 0.8689        | 3.0   | 771  | 0.4490          | 0.7911    | 0.8590 | 0.8148 | 0.8599   |
+| 0.2702        | 4.0   | 1028 | 0.4748          | 0.8291    | 0.8689 | 0.8457 | 0.8730   |
+| 0.2702        | 5.0   | 1285 | 0.5217          | 0.8326    | 0.8543 | 0.8413 | 0.8783   |
+| 0.1505        | 6.0   | 1542 | 0.5288          | 0.8351    | 0.8650 | 0.8481 | 0.8754   |
+| 0.1505        | 7.0   | 1799 | 0.5801          | 0.8417    | 0.8585 | 0.8487 | 0.8769   |
+| 0.092         | 8.0   | 2056 | 0.5721          | 0.8402    | 0.8694 | 0.8535 | 0.8818   |
+| 0.092         | 9.0   | 2313 | 0.6135          | 0.8453    | 0.8618 | 0.8522 | 0.8808   |
+| 0.0723        | 10.0  | 2570 | 0.6213          | 0.8399    | 0.8622 | 0.8498 | 0.8798   |
 ### Framework versions