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README.md

@@ -9,13 +9,13 @@ datasets:
 - disham993/ElectricalNER
 metrics:
 - epoch: 1.0
-- eval_precision: 0.8651061595018381
-- eval_recall: 0.9113253773808584
-- eval_f1: 0.8876145023477792
-- eval_accuracy: 0.9507711918419376
-- eval_runtime: 1.7666
-- eval_samples_per_second: 854.191
-- eval_steps_per_second: 13.586
+- eval_precision: 0.8758209405903223
+- eval_recall: 0.9169366948549752
+- eval_f1: 0.8959073359073358
+- eval_accuracy: 0.9532186105799872
+- eval_runtime: 1.7541
+- eval_samples_per_second: 860.279
+- eval_steps_per_second: 13.682
 ---
 
 # disham993/electrical-ner-distilbert-base
@@ -41,7 +41,7 @@ The model was trained on the disham993/ElectricalNER dataset.
 
 ## Evaluation results
 
-### Metrics\n- epoch: 1.0\n- eval_precision: 0.8651061595018381\n- eval_recall: 0.9113253773808584\n- eval_f1: 0.8876145023477792\n- eval_accuracy: 0.9507711918419376\n- eval_runtime: 1.7666\n- eval_samples_per_second: 854.191\n- eval_steps_per_second: 13.586
+### Metrics\n- epoch: 1.0\n- eval_precision: 0.8758209405903223\n- eval_recall: 0.9169366948549752\n- eval_f1: 0.8959073359073358\n- eval_accuracy: 0.9532186105799872\n- eval_runtime: 1.7541\n- eval_samples_per_second: 860.279\n- eval_steps_per_second: 13.682
 
 ## Usage