End of training

README.md

@@ -4,9 +4,7 @@ base_model: google-bert/bert-base-uncased
 tags:
 - generated_from_trainer
 metrics:
-- precision
-- recall
-- f1
+- accuracy
 model-index:
 - name: Aroma-classifier
   results: []
@@ -19,10 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7405
-- Precision: 0.8273
-- Recall: 0.8268
-- F1: 0.8270
+- Loss: 0.5282
+- Accuracy: 0.8372
 
 ## Model description
 
@@ -51,11 +47,11 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
-| 0.4369        | 1.0   | 2375 | 0.5383          | 0.8841    | 0.6854 | 0.7722 |
-| 0.3339        | 2.0   | 4750 | 0.5662          | 0.8410    | 0.8102 | 0.8253 |
-| 0.2333        | 3.0   | 7125 | 0.7405          | 0.8273    | 0.8268 | 0.8270 |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.437         | 1.0   | 2500 | 0.3961          | 0.8325   |
+| 0.4026        | 2.0   | 5000 | 0.4057          | 0.8377   |
+| 0.3329        | 3.0   | 7500 | 0.5282          | 0.8372   |
 
 
 ### Framework versions

model.safetensors

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training_args.bin

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