LovenOO
/

distilBERT_without_preprocessing_grid_search

@@ -20,10 +20,10 @@ 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: 0.7297
-- Precision: 0.8417
-- Recall: 0.8510
-- F1: 0.8460
 - Accuracy: 0.8793
 ## 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   | 257  | 0.4958          | 0.7757    | 0.8526 | 0.8027 | 0.8526   |
-| 0.6647        | 2.0   | 514  | 0.4756          | 0.8336    | 0.8480 | 0.8386 | 0.8701   |
-| 0.6647        | 3.0   | 771  | 0.4823          | 0.8197    | 0.8588 | 0.8360 | 0.8730   |
-| 0.2305        | 4.0   | 1028 | 0.5479          | 0.8314    | 0.8618 | 0.8439 | 0.8735   |
-| 0.2305        | 5.0   | 1285 | 0.5832          | 0.8295    | 0.8542 | 0.8401 | 0.8779   |
-| 0.1282        | 6.0   | 1542 | 0.5929          | 0.8251    | 0.8627 | 0.8404 | 0.8745   |
-| 0.1282        | 7.0   | 1799 | 0.7066          | 0.8476    | 0.8496 | 0.8472 | 0.8774   |
-| 0.0828        | 8.0   | 2056 | 0.6873          | 0.8392    | 0.8510 | 0.8448 | 0.8764   |
-| 0.0828        | 9.0   | 2313 | 0.7189          | 0.8410    | 0.8524 | 0.8461 | 0.8788   |
-| 0.0566        | 10.0  | 2570 | 0.7297          | 0.8417    | 0.8510 | 0.8460 | 0.8793   |
 ### 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: 0.6943
+- Precision: 0.8467
+- Recall: 0.8562
+- F1: 0.8509
 - Accuracy: 0.8793
 ## 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   | 257  | 0.5790          | 0.7659    | 0.8225 | 0.7875 | 0.8472   |
+| 0.7473        | 2.0   | 514  | 0.5007          | 0.8115    | 0.8503 | 0.8264 | 0.8647   |
+| 0.7473        | 3.0   | 771  | 0.4903          | 0.8007    | 0.8418 | 0.8174 | 0.8594   |
+| 0.2608        | 4.0   | 1028 | 0.5370          | 0.8249    | 0.8491 | 0.8350 | 0.8657   |
+| 0.2608        | 5.0   | 1285 | 0.6034          | 0.8424    | 0.8514 | 0.8455 | 0.8803   |
+| 0.1543        | 6.0   | 1542 | 0.5988          | 0.8396    | 0.8565 | 0.8466 | 0.8788   |
+| 0.1543        | 7.0   | 1799 | 0.6736          | 0.8486    | 0.8453 | 0.8458 | 0.8769   |
+| 0.0981        | 8.0   | 2056 | 0.6476          | 0.8400    | 0.8605 | 0.8492 | 0.8788   |
+| 0.0981        | 9.0   | 2313 | 0.6837          | 0.8443    | 0.8510 | 0.8469 | 0.8788   |
+| 0.0713        | 10.0  | 2570 | 0.6943          | 0.8467    | 0.8562 | 0.8509 | 0.8793   |
 ### Framework versions