FareehaAly
/

fator-argument-quality

Text Classification

Generated from Trainer

text-embeddings-inference

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FareehaAly commited on Apr 21

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@@ -20,8 +20,8 @@ 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: 0.5797
-- Accuracy: 0.7814
-- F1 Macro: 0.4606
 - F1 Weighted: 0.7459
 ## Model description
@@ -56,10 +56,10 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
 | 0.5548        | 1.0   | 558  | 0.5412          | 0.7741   | 0.3669   | 0.7188      |
-| 0.4892        | 2.0   | 1116 | 0.5830          | 0.7766   | 0.3644   | 0.7055      |
-| 0.4455        | 3.0   | 1674 | 0.5797          | 0.7814   | 0.4606   | 0.7459      |
-| 0.3561        | 4.0   | 2232 | 0.6330          | 0.7772   | 0.466    | 0.7457      |
-| 0.3084        | 5.0   | 2790 | 0.6744          | 0.7757   | 0.4695   | 0.745       |
 ### Framework versions

 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: 0.5797
+- Accuracy: 0.8014
+- F1 Macro: 0.5806
 - F1 Weighted: 0.7459
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
 | 0.5548        | 1.0   | 558  | 0.5412          | 0.7741   | 0.3669   | 0.7188      |
+| 0.4892        | 2.0   | 1116 | 0.5830          | 0.7866   | 0.3644   | 0.7055      |
+| 0.4455        | 3.0   | 1674 | 0.5797          | 0.7814   | 0.4606   | 0.7449      |
+| 0.3561        | 4.0   | 2232 | 0.6330          | 0.7902   | 0.4996    | 0.7457      |
+| 0.3084        | 5.0   | 2790 | 0.6744          | 0.8057   | 0.5806   | 0.7459       |
 ### Framework versions