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camembert-ner-finetuned-ner

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deepaksiloka commited on Oct 4, 2022

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@@ -18,11 +18,11 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0862
-- Precision: 0.9925
-- Recall: 0.9959
-- F1: 0.9942
-- Accuracy: 0.9896
 ## Model description
@@ -47,22 +47,17 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 10
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.1364        | 1.0   | 769  | 0.0832          | 0.9828    | 0.9998 | 0.9912 | 0.9823   |
-| 0.0533        | 2.0   | 1538 | 0.0631          | 0.9934    | 0.9923 | 0.9928 | 0.9871   |
-| 0.0329        | 3.0   | 2307 | 0.0651          | 0.9912    | 0.9978 | 0.9945 | 0.9897   |
-| 0.021         | 4.0   | 3076 | 0.0680          | 0.9937    | 0.9952 | 0.9945 | 0.9899   |
-| 0.0171        | 5.0   | 3845 | 0.0628          | 0.9928    | 0.9969 | 0.9948 | 0.9906   |
-| 0.0115        | 6.0   | 4614 | 0.0678          | 0.9930    | 0.9963 | 0.9947 | 0.9903   |
-| 0.0075        | 7.0   | 5383 | 0.0854          | 0.9928    | 0.9956 | 0.9942 | 0.9896   |
-| 0.0045        | 8.0   | 6152 | 0.0862          | 0.9919    | 0.9948 | 0.9934 | 0.9890   |
-| 0.0031        | 9.0   | 6921 | 0.0839          | 0.9919    | 0.9958 | 0.9938 | 0.9896   |
-| 0.0028        | 10.0  | 7690 | 0.0862          | 0.9925    | 0.9959 | 0.9942 | 0.9896   |
 ### Framework versions

 This model is a fine-tuned version of [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.1258
+- Precision: 0.9791
+- Recall: 0.9723
+- F1: 0.9757
+- Accuracy: 0.9775
 ## Model description
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
+- num_epochs: 5
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 219  | 0.1130          | 0.9569    | 0.9723 | 0.9645 | 0.9687   |
+| No log        | 2.0   | 438  | 0.1681          | 0.9528    | 0.9769 | 0.9647 | 0.9646   |
+| 0.1656        | 3.0   | 657  | 0.1253          | 0.9693    | 0.9827 | 0.9759 | 0.9779   |
+| 0.1656        | 4.0   | 876  | 0.1230          | 0.9692    | 0.9804 | 0.9748 | 0.9783   |
+| 0.047         | 5.0   | 1095 | 0.1258          | 0.9791    | 0.9723 | 0.9757 | 0.9775   |
 ### Framework versions