Fix test set result

README.md

@@ -17,13 +17,13 @@ model-index:
       revision: 2814b78e7af4b5a1f1886fe7ad49632de4d9dd25
     metrics:
     - type: f1
-      value: 0.9261
+      value: 0.9270
       name: F1
     - type: precision
-      value: 0.9242
+      value: 0.9281
       name: Precision
     - type: recall
-      value: 0.9281
+      value: 0.9259
       name: Recall
 license: apache-2.0
 datasets:
@@ -52,13 +52,23 @@ should probably proofread and complete it, then remove this comment. -->
 # span-marker-bert-base-multilingual-cased-multinerd
 
 This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an [Babelscape/multinerd](https://huggingface.co/datasets/Babelscape/multinerd) dataset.
-It achieves the following results on the test set:
+It achieves the following results on the evaluation set:
 - Loss: 0.0049
 - Overall Precision: 0.9242
 - Overall Recall: 0.9281
 - Overall F1: 0.9261
 - Overall Accuracy: 0.9852
 
+Test set results:
+- test_loss: 0.005226554349064827,
+- test_overall_accuracy: 0.9851129807294873,
+- test_overall_f1: 0.9270450073152169,
+- test_overall_precision: 0.9281906912835416,
+- test_overall_recall: 0.9259021481405626,
+- test_runtime: 2690.9722,
+- test_samples_per_second: 150.748,
+- test_steps_per_second: 4.711
+
 
 This is a replication of Tom's work. Everything remains unchanged, 
 except that we extended the number of training epochs to 3 for a