update model card README.md

README.md

@@ -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: 0.0012
-- Precision: 1.0
-- Recall: 1.0
-- F1: 1.0
-- Accuracy: 1.0
+- Loss: 0.0862
+- Precision: 0.9925
+- Recall: 0.9959
+- F1: 0.9942
+- Accuracy: 0.9896
 
 ## Model description
 
@@ -47,15 +47,22 @@ 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: 3
+- num_epochs: 10
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
-| No log        | 1.0   | 5    | 0.0179          | 1.0       | 1.0    | 1.0 | 1.0      |
-| No log        | 2.0   | 10   | 0.0016          | 1.0       | 1.0    | 1.0 | 1.0      |
-| No log        | 3.0   | 15   | 0.0012          | 1.0       | 1.0    | 1.0 | 1.0      |
+| 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