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DeBERTa-finetuned-ner-S800

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ViktorDo commited on Sep 5, 2023

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@@ -1,6 +1,6 @@
 ---
 license: mit
-base_model: microsoft/deberta-v3-small
 tags:
 - generated_from_trainer
 metrics:
@@ -18,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 # DeBERTa-finetuned-ner-S800
-This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0636
-- Precision: 0.6312
-- Recall: 0.7311
-- F1: 0.6775
-- Accuracy: 0.9769
 ## Model description
@@ -55,11 +55,11 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 55   | 0.0843          | 0.4846    | 0.5294 | 0.5060 | 0.9683   |
-| No log        | 2.0   | 110  | 0.0697          | 0.5695    | 0.7115 | 0.6326 | 0.9729   |
-| No log        | 3.0   | 165  | 0.0652          | 0.6099    | 0.7423 | 0.6696 | 0.9754   |
-| No log        | 4.0   | 220  | 0.0636          | 0.6445    | 0.7185 | 0.6795 | 0.9772   |
-| No log        | 5.0   | 275  | 0.0636          | 0.6312    | 0.7311 | 0.6775 | 0.9769   |
 ### Framework versions

 ---
 license: mit
+base_model: microsoft/deberta-v3-base
 tags:
 - generated_from_trainer
 metrics:
 # DeBERTa-finetuned-ner-S800
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.0681
+- Precision: 0.6874
+- Recall: 0.7731
+- F1: 0.7278
+- Accuracy: 0.9771
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 55   | 0.0748          | 0.5784    | 0.6457 | 0.6102 | 0.9699   |
+| No log        | 2.0   | 110  | 0.0709          | 0.6174    | 0.7773 | 0.6882 | 0.9750   |
+| No log        | 3.0   | 165  | 0.0670          | 0.6460    | 0.7899 | 0.7108 | 0.9758   |
+| No log        | 4.0   | 220  | 0.0628          | 0.6966    | 0.7717 | 0.7322 | 0.9775   |
+| No log        | 5.0   | 275  | 0.0681          | 0.6874    | 0.7731 | 0.7278 | 0.9771   |
 ### Framework versions