NTCAL
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norbert2_sentiment_norec_12

Text Classification

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text-embeddings-inference

Model card Files Files and versions

simenaabol commited on Mar 7, 2023

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update model card README.md

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@@ -18,14 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5871
-- Start: ------------------------------------------------------------
 - Accuracy: 0.8
 - Balanced Accuracy: 0.5
 - F1 Score: 0.8889
 - Recall: 1.0
 - Precision: 0.8
-- End: ------------------------------------------------------------
 ## Model description
@@ -54,10 +53,10 @@ The following hyperparameters were used during training:
 ### Training results
-| Training Loss | Epoch | Step | Validation Loss | Start                                                        | Accuracy | Balanced Accuracy | F1 Score | Recall | Precision | End                                                          |
-|:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------:|:--------:|:-----------------:|:--------:|:------:|:---------:|:------------------------------------------------------------:|
-| 0.8014        | 1.0   | 5    | 0.6713          | ------------------------------------------------------------ | 0.6      | 0.375             | 0.75     | 0.75   | 0.75      | ------------------------------------------------------------ |
-| 0.256         | 2.0   | 10   | 0.5871          | ------------------------------------------------------------ | 0.8      | 0.5               | 0.8889   | 1.0    | 0.8       | ------------------------------------------------------------ |
 ### Framework versions

 This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.4914
+- Compute Metrics: :
 - Accuracy: 0.8
 - Balanced Accuracy: 0.5
 - F1 Score: 0.8889
 - Recall: 1.0
 - Precision: 0.8
 ## Model description
 ### Training results
+| Training Loss | Epoch | Step | Validation Loss | Compute Metrics | Accuracy | Balanced Accuracy | F1 Score | Recall | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:---------------:|:--------:|:-----------------:|:--------:|:------:|:---------:|
+| 0.4908        | 1.0   | 5    | 0.4910          | :               | 0.8      | 0.5               | 0.8889   | 1.0    | 0.8       |
+| 0.3751        | 2.0   | 10   | 0.4914          | :               | 0.8      | 0.5               | 0.8889   | 1.0    | 0.8       |
 ### Framework versions