update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.4158878504672897
+      value: 0.29015544041450775
     - name: Recall
       type: recall
-      value: 0.5028248587570622
+      value: 0.27722772277227725
     - name: F1
       type: f1
-      value: 0.45524296675191817
+      value: 0.2835443037974684
     - name: Accuracy
       type: accuracy
-      value: 0.8060836501901141
+      value: 0.7297843665768194
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,11 +43,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the lg-ner dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7681
-- Precision: 0.4159
-- Recall: 0.5028
-- F1: 0.4552
-- Accuracy: 0.8061
+- Loss: 1.0530
+- Precision: 0.2902
+- Recall: 0.2772
+- F1: 0.2835
+- Accuracy: 0.7298
 
 ## Model description
 
@@ -78,16 +78,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 25   | 0.9702          | 0.2686    | 0.3672 | 0.3103 | 0.7240   |
-| No log        | 2.0   | 50   | 0.8977          | 0.2702    | 0.3785 | 0.3153 | 0.7468   |
-| No log        | 3.0   | 75   | 0.8785          | 0.2517    | 0.4124 | 0.3126 | 0.7551   |
-| No log        | 4.0   | 100  | 0.8608          | 0.2927    | 0.4746 | 0.3621 | 0.7567   |
-| No log        | 5.0   | 125  | 0.7859          | 0.4053    | 0.4350 | 0.4196 | 0.7909   |
-| No log        | 6.0   | 150  | 0.7728          | 0.4010    | 0.4350 | 0.4173 | 0.7901   |
-| No log        | 7.0   | 175  | 0.7647          | 0.4118    | 0.4746 | 0.4409 | 0.7932   |
-| No log        | 8.0   | 200  | 0.7800          | 0.3929    | 0.4972 | 0.4389 | 0.7985   |
-| No log        | 9.0   | 225  | 0.7706          | 0.4211    | 0.4972 | 0.4560 | 0.8053   |
-| No log        | 10.0  | 250  | 0.7681          | 0.4159    | 0.5028 | 0.4552 | 0.8061   |
+| No log        | 1.0   | 25   | 1.2878          | 0.0       | 0.0    | 0.0    | 0.7271   |
+| No log        | 2.0   | 50   | 1.2373          | 0.0       | 0.0    | 0.0    | 0.7271   |
+| No log        | 3.0   | 75   | 1.2309          | 0.3542    | 0.1683 | 0.2282 | 0.7244   |
+| No log        | 4.0   | 100  | 1.1505          | 0.2712    | 0.2376 | 0.2533 | 0.7183   |
+| No log        | 5.0   | 125  | 1.1360          | 0.2579    | 0.2426 | 0.25   | 0.7170   |
+| No log        | 6.0   | 150  | 1.0932          | 0.3108    | 0.2277 | 0.2629 | 0.7338   |
+| No log        | 7.0   | 175  | 1.0761          | 0.2989    | 0.2574 | 0.2766 | 0.7298   |
+| No log        | 8.0   | 200  | 1.0645          | 0.2805    | 0.3069 | 0.2931 | 0.7244   |
+| No log        | 9.0   | 225  | 1.0577          | 0.3022    | 0.2723 | 0.2865 | 0.7325   |
+| No log        | 10.0  | 250  | 1.0530          | 0.2902    | 0.2772 | 0.2835 | 0.7298   |
 
 
 ### Framework versions