tiagoblima
/

newsdata-bert

Text Classification

Generated from Trainer

Inference Endpoints

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tiagoblima commited on Jun 24

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3e958e0

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1 Parent(s): 258629e

End of training

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@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.0878
-- Accuracy: 0.8087
 ## Model description
@@ -49,17 +49,17 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
 |:-------------:|:------:|:-----:|:---------------:|:--------:|
-| 1.3096        | 0.0859 | 5000  | 1.4907          | 0.7014   |
-| 1.2402        | 0.1718 | 10000 | 1.2411          | 0.7285   |
-| 1.1273        | 0.2577 | 15000 | 1.3464          | 0.7514   |
-| 1.0028        | 0.3436 | 20000 | 1.4583          | 0.7323   |
-| 0.9333        | 0.4295 | 25000 | 1.2102          | 0.7713   |
-| 0.9045        | 0.5155 | 30000 | 1.1515          | 0.7801   |
-| 0.7642        | 0.6014 | 35000 | 1.1968          | 0.7873   |
-| 0.8657        | 0.6873 | 40000 | 1.0961          | 0.7967   |
-| 0.8082        | 0.7732 | 45000 | 1.1199          | 0.7977   |
-| 0.7657        | 0.8591 | 50000 | 1.1115          | 0.8029   |
-| 0.7556        | 0.9450 | 55000 | 1.0878          | 0.8087   |
 ### Framework versions

 This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.7534
+- Accuracy: 0.8531
 ## Model description
 | Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
 |:-------------:|:------:|:-----:|:---------------:|:--------:|
+| 1.4704        | 0.0859 | 5000  | 1.4487          | 0.6858   |
+| 1.1946        | 0.1718 | 10000 | 1.2197          | 0.7417   |
+| 1.1323        | 0.2577 | 15000 | 0.9984          | 0.7733   |
+| 0.9926        | 0.3436 | 20000 | 1.0195          | 0.7901   |
+| 0.9232        | 0.4295 | 25000 | 0.9879          | 0.8089   |
+| 0.9273        | 0.5155 | 30000 | 0.8956          | 0.8224   |
+| 1.0023        | 0.6014 | 35000 | 0.8435          | 0.8277   |
+| 0.7566        | 0.6873 | 40000 | 0.8668          | 0.8331   |
+| 0.9032        | 0.7732 | 45000 | 0.8221          | 0.8408   |
+| 0.7227        | 0.8591 | 50000 | 0.7653          | 0.8456   |
+| 0.8159        | 0.9450 | 55000 | 0.7534          | 0.8531   |
 ### Framework versions