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benchmark_config.yaml

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+model:
+  base_url: "http://127.0.0.1:8000"
+  max_tokens: 512
+  temperature: 0.1
+  timeout: 30
+
+datasets:
+  benchmark_dataset:
+    file_path: "ner_benchmark_dataset.jsonl"
+    sample_size: 100  # Use first 100 examples for quick benchmarking
+    instruction_field: "instruction"
+    input_field: "input"
+    expected_output_field: "response"
+
+metrics:
+  # Primary metrics for HuggingFace
+  entity_recognition:
+    name: "Entity Recognition F1 Score"
+    description: "F1 score for named entity recognition accuracy"
+    type: "f1"
+
+  precision:
+    name: "Precision Score"
+    description: "Precision for entity recognition"
+    type: "precision"
+
+  recall:
+    name: "Recall Score"
+    description: "Recall for entity recognition"
+    type: "recall"
+
+  latency:
+    name: "Average Latency"
+    description: "Average response time in milliseconds"
+    type: "latency"
+
+  # Entity type specific performance
+  entity_types:
+    person:
+      name: "Person Entity Recognition"
+      keywords: ["PERSON", "person", "Person"]
+    organization:
+      name: "Organization Entity Recognition"
+      keywords: ["ORG", "organization", "Organization"]
+    location:
+      name: "Location Entity Recognition"
+      keywords: ["LOC", "location", "Location"]
+    miscellaneous:
+      name: "Miscellaneous Entity Recognition"
+      keywords: ["MISC", "miscellaneous", "Miscellaneous"]
+
+output:
+  results_file: "benchmarks.txt"
+  detailed_results_file: "benchmark_results.json"
+  include_examples: true
+  max_examples: 10