End of training

README.md

@@ -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: 1.3584
-- Precision: 0.5891
-- Recall: 0.5714
-- F1: 0.5512
-- Accuracy: 0.5714
+- Loss: 0.6563
+- Precision: 0.7749
+- Recall: 0.7703
+- F1: 0.7689
+- Accuracy: 0.7703
 
 ## Model description
 
@@ -43,9 +43,9 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 64
-- eval_batch_size: 64
+- learning_rate: 5e-05
+- train_batch_size: 200
+- eval_batch_size: 200
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -55,9 +55,7 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 1.9209        | 1.07  | 30   | 1.8358          | 0.3662    | 0.3585 | 0.3023 | 0.3585   |
-| 1.7002        | 2.14  | 60   | 1.5497          | 0.5778    | 0.5182 | 0.4904 | 0.5182   |
-| 1.4562        | 3.21  | 90   | 1.3981          | 0.6130    | 0.5742 | 0.5583 | 0.5742   |
+| 0.3132        | 3.33  | 30   | 0.6568          | 0.7782    | 0.7731 | 0.7720 | 0.7731   |
 
 
 ### Framework versions

model.safetensors

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training_args.bin

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