End of training

README.md

@@ -1,6 +1,6 @@
 ---
 license: apache-2.0
-base_model: casual/nlp_til2
+base_model: distilbert/distilbert-base-uncased
 tags:
 - generated_from_trainer
 metrics:
@@ -18,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # nlp_til3
 
-This model is a fine-tuned version of [casual/nlp_til2](https://huggingface.co/casual/nlp_til2) on an unknown dataset.
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0052
-- Precision: 0.9899
-- Recall: 0.9919
-- F1: 0.9909
-- Accuracy: 0.9983
+- Loss: 0.0001
+- Precision: 1.0
+- Recall: 1.0
+- F1: 1.0
+- Accuracy: 1.0
 
 ## Model description
 
@@ -49,22 +49,17 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 10
+- num_epochs: 5
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 219  | 0.0192          | 0.9571    | 0.9614 | 0.9592 | 0.9931   |
-| No log        | 2.0   | 438  | 0.0176          | 0.9607    | 0.9696 | 0.9652 | 0.9940   |
-| 0.0238        | 3.0   | 657  | 0.0142          | 0.9702    | 0.9692 | 0.9697 | 0.9948   |
-| 0.0238        | 4.0   | 876  | 0.0105          | 0.9764    | 0.9744 | 0.9754 | 0.9958   |
-| 0.0201        | 5.0   | 1095 | 0.0093          | 0.9839    | 0.9804 | 0.9822 | 0.9969   |
-| 0.0201        | 6.0   | 1314 | 0.0080          | 0.9832    | 0.9878 | 0.9855 | 0.9974   |
-| 0.0147        | 7.0   | 1533 | 0.0078          | 0.9850    | 0.9858 | 0.9854 | 0.9975   |
-| 0.0147        | 8.0   | 1752 | 0.0071          | 0.9835    | 0.9892 | 0.9863 | 0.9976   |
-| 0.0147        | 9.0   | 1971 | 0.0053          | 0.9899    | 0.9911 | 0.9905 | 0.9983   |
-| 0.0106        | 10.0  | 2190 | 0.0052          | 0.9899    | 0.9919 | 0.9909 | 0.9983   |
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
+| No log        | 1.0   | 219  | 0.0005          | 1.0       | 1.0    | 1.0 | 1.0      |
+| No log        | 2.0   | 438  | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
+| 0.0312        | 3.0   | 657  | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
+| 0.0312        | 4.0   | 876  | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
+| 0.0004        | 5.0   | 1095 | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
 
 
 ### Framework versions