LovenOO
/

distilBERT_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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8262
-- Precision: 0.8491
-- Recall: 0.8536
-- F1: 0.8511
-- Accuracy: 0.8837
 ## 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: 16
 - eval_batch_size: 16
 - seed: 42
@@ -55,16 +55,16 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.8922        | 1.0   | 514  | 0.5350          | 0.7953    | 0.8363 | 0.8092 | 0.8628   |
-| 0.4521        | 2.0   | 1028 | 0.5359          | 0.8214    | 0.8385 | 0.8282 | 0.8652   |
-| 0.2928        | 3.0   | 1542 | 0.5876          | 0.8264    | 0.8504 | 0.8367 | 0.8798   |
-| 0.2099        | 4.0   | 2056 | 0.6974          | 0.8288    | 0.8435 | 0.8351 | 0.8764   |
-| 0.1531        | 5.0   | 2570 | 0.8245          | 0.8367    | 0.8125 | 0.8232 | 0.8710   |
-| 0.1124        | 6.0   | 3084 | 0.7553          | 0.8349    | 0.8543 | 0.8435 | 0.8764   |
-| 0.1045        | 7.0   | 3598 | 0.7912          | 0.8452    | 0.8538 | 0.8492 | 0.8822   |
-| 0.0716        | 8.0   | 4112 | 0.7909          | 0.8422    | 0.8529 | 0.8471 | 0.8788   |
-| 0.0746        | 9.0   | 4626 | 0.8364          | 0.8462    | 0.8458 | 0.8458 | 0.8779   |
-| 0.0533        | 10.0  | 5140 | 0.8262          | 0.8491    | 0.8536 | 0.8511 | 0.8837   |
 ### Framework versions

 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.7859
+- Precision: 0.8423
+- Recall: 0.8487
+- F1: 0.8452
+- Accuracy: 0.8769
 ## Model description
 ### Training hyperparameters
 The following hyperparameters were used during training:
+- learning_rate: 3e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.908         | 1.0   | 514  | 0.5671          | 0.7815    | 0.8256 | 0.7960 | 0.8511   |
+| 0.4351        | 2.0   | 1028 | 0.5301          | 0.8371    | 0.8439 | 0.8400 | 0.8715   |
+| 0.2993        | 3.0   | 1542 | 0.5461          | 0.8250    | 0.8605 | 0.8401 | 0.8754   |
+| 0.2186        | 4.0   | 2056 | 0.6724          | 0.8348    | 0.8517 | 0.8417 | 0.8745   |
+| 0.168         | 5.0   | 2570 | 0.6923          | 0.8410    | 0.8441 | 0.8417 | 0.8754   |
+| 0.1302        | 6.0   | 3084 | 0.6834          | 0.8301    | 0.8600 | 0.8432 | 0.8740   |
+| 0.1094        | 7.0   | 3598 | 0.7413          | 0.8400    | 0.8515 | 0.8453 | 0.8774   |
+| 0.0876        | 8.0   | 4112 | 0.7654          | 0.8383    | 0.8529 | 0.8452 | 0.8788   |
+| 0.0833        | 9.0   | 4626 | 0.7748          | 0.8474    | 0.8530 | 0.8499 | 0.8798   |
+| 0.0593        | 10.0  | 5140 | 0.7859          | 0.8423    | 0.8487 | 0.8452 | 0.8769   |
 ### Framework versions