Upload perturb_029_seed_1631871586_sigma_0p0005/validation/cache/reports/granite-4.0-8b-preview-r260310a/bfcl_v4.json with huggingface_hub
Browse files
perturb_029_seed_1631871586_sigma_0p0005/validation/cache/reports/granite-4.0-8b-preview-r260310a/bfcl_v4.json
ADDED
|
@@ -0,0 +1,188 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"name": "granite-4.0-8b-preview-r260310a@bfcl_v4",
|
| 3 |
+
"dataset_name": "bfcl_v4",
|
| 4 |
+
"dataset_pretty_name": "BFCL-v4",
|
| 5 |
+
"dataset_description": "\n## Overview\n\nBFCL-v4 (Berkeley Function-Calling Leaderboard V4) is a comprehensive benchmark for evaluating agentic function-calling capabilities of LLMs. It tests web search, memory operations, and format sensitivity as building blocks for agentic applications.\n\n## Task Description\n\n- **Task Type**: Agentic Function Calling Evaluation\n- **Input**: Scenarios requiring function calls for web search, memory, etc.\n- **Output**: Correct function calls with proper arguments\n- **Capabilities**: Web search, memory read/write, format handling\n\n## Key Features\n\n- Holistic agentic evaluation framework\n- Tests building blocks for LLM agents (search, memory, formatting)\n- Multiple scoring categories for detailed analysis\n- Supports both FC models and non-FC models\n- Optional web search with SerpAPI integration\n\n## Evaluation Notes\n\n- **Installation Required**: `pip install bfcl-eval==2025.10.27.1`\n- Primary metric: **Accuracy** per category\n- Configure `is_fc_model` based on model capabilities\n- Optional: Set `SERPAPI_API_KEY` for web search tasks\n- [Usage Example](https://evalscope.readthedocs.io/en/latest/third_party/bfcl_v4.html)\n",
|
| 6 |
+
"model_name": "granite-4.0-8b-preview-r260310a",
|
| 7 |
+
"score": 0.5315,
|
| 8 |
+
"metrics": [
|
| 9 |
+
{
|
| 10 |
+
"name": "acc",
|
| 11 |
+
"num": 2190,
|
| 12 |
+
"score": 0.5315,
|
| 13 |
+
"macro_score": 0.5315,
|
| 14 |
+
"categories": [
|
| 15 |
+
{
|
| 16 |
+
"name": [
|
| 17 |
+
"default"
|
| 18 |
+
],
|
| 19 |
+
"num": 2190,
|
| 20 |
+
"score": 0.5315,
|
| 21 |
+
"macro_score": 0.4782,
|
| 22 |
+
"subsets": [
|
| 23 |
+
{
|
| 24 |
+
"name": "irrelevance",
|
| 25 |
+
"score": 0.825,
|
| 26 |
+
"num": 240,
|
| 27 |
+
"is_aggregate": false
|
| 28 |
+
},
|
| 29 |
+
{
|
| 30 |
+
"name": "multi_turn_base",
|
| 31 |
+
"score": 0.075,
|
| 32 |
+
"num": 200,
|
| 33 |
+
"is_aggregate": false
|
| 34 |
+
},
|
| 35 |
+
{
|
| 36 |
+
"name": "multi_turn_long_context",
|
| 37 |
+
"score": 0.03,
|
| 38 |
+
"num": 200,
|
| 39 |
+
"is_aggregate": false
|
| 40 |
+
},
|
| 41 |
+
{
|
| 42 |
+
"name": "multi_turn_miss_func",
|
| 43 |
+
"score": 0.035,
|
| 44 |
+
"num": 200,
|
| 45 |
+
"is_aggregate": false
|
| 46 |
+
},
|
| 47 |
+
{
|
| 48 |
+
"name": "multi_turn_miss_param",
|
| 49 |
+
"score": 0.04,
|
| 50 |
+
"num": 200,
|
| 51 |
+
"is_aggregate": false
|
| 52 |
+
},
|
| 53 |
+
{
|
| 54 |
+
"name": "multiple",
|
| 55 |
+
"score": 0.915,
|
| 56 |
+
"num": 200,
|
| 57 |
+
"is_aggregate": false
|
| 58 |
+
},
|
| 59 |
+
{
|
| 60 |
+
"name": "parallel",
|
| 61 |
+
"score": 0.83,
|
| 62 |
+
"num": 200,
|
| 63 |
+
"is_aggregate": false
|
| 64 |
+
},
|
| 65 |
+
{
|
| 66 |
+
"name": "parallel_multiple",
|
| 67 |
+
"score": 0.775,
|
| 68 |
+
"num": 200,
|
| 69 |
+
"is_aggregate": false
|
| 70 |
+
},
|
| 71 |
+
{
|
| 72 |
+
"name": "simple_java",
|
| 73 |
+
"score": 0.38,
|
| 74 |
+
"num": 100,
|
| 75 |
+
"is_aggregate": false
|
| 76 |
+
},
|
| 77 |
+
{
|
| 78 |
+
"name": "simple_javascript",
|
| 79 |
+
"score": 0.44,
|
| 80 |
+
"num": 50,
|
| 81 |
+
"is_aggregate": false
|
| 82 |
+
},
|
| 83 |
+
{
|
| 84 |
+
"name": "simple_python",
|
| 85 |
+
"score": 0.915,
|
| 86 |
+
"num": 400,
|
| 87 |
+
"is_aggregate": false
|
| 88 |
+
}
|
| 89 |
+
]
|
| 90 |
+
},
|
| 91 |
+
{
|
| 92 |
+
"name": [
|
| 93 |
+
"-"
|
| 94 |
+
],
|
| 95 |
+
"num": 0,
|
| 96 |
+
"score": 0.0,
|
| 97 |
+
"macro_score": 0.0,
|
| 98 |
+
"subsets": [
|
| 99 |
+
{
|
| 100 |
+
"name": "MULTI_TURN",
|
| 101 |
+
"score": 0.045,
|
| 102 |
+
"num": 800,
|
| 103 |
+
"is_aggregate": true
|
| 104 |
+
},
|
| 105 |
+
{
|
| 106 |
+
"name": "NON_LIVE",
|
| 107 |
+
"score": 0.7746,
|
| 108 |
+
"num": 1150,
|
| 109 |
+
"is_aggregate": true
|
| 110 |
+
},
|
| 111 |
+
{
|
| 112 |
+
"name": "HALLUCINATION",
|
| 113 |
+
"score": 0.825,
|
| 114 |
+
"num": 240,
|
| 115 |
+
"is_aggregate": true
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"name": "OVERALL",
|
| 119 |
+
"score": 0.1735,
|
| 120 |
+
"num": 2190,
|
| 121 |
+
"is_aggregate": true
|
| 122 |
+
}
|
| 123 |
+
]
|
| 124 |
+
}
|
| 125 |
+
]
|
| 126 |
+
}
|
| 127 |
+
],
|
| 128 |
+
"analysis": "N/A",
|
| 129 |
+
"perf_metrics": {
|
| 130 |
+
"summary": {
|
| 131 |
+
"n_samples": 8629,
|
| 132 |
+
"latency": {
|
| 133 |
+
"mean": 1.734142,
|
| 134 |
+
"std": 11.053449,
|
| 135 |
+
"min": 0.079596,
|
| 136 |
+
"25%": 0.663944,
|
| 137 |
+
"50%": 1.038139,
|
| 138 |
+
"75%": 1.681474,
|
| 139 |
+
"90%": 2.701772,
|
| 140 |
+
"99%": 7.652362,
|
| 141 |
+
"max": 704.445093
|
| 142 |
+
},
|
| 143 |
+
"throughput": {
|
| 144 |
+
"avg_output_tps": 45.14,
|
| 145 |
+
"avg_req_ps": 0.5767
|
| 146 |
+
},
|
| 147 |
+
"usage": {
|
| 148 |
+
"input_tokens": {
|
| 149 |
+
"mean": 6854.315911,
|
| 150 |
+
"std": 5533.622291,
|
| 151 |
+
"min": 237.0,
|
| 152 |
+
"25%": 4743.0,
|
| 153 |
+
"50%": 7012.0,
|
| 154 |
+
"75%": 8681.0,
|
| 155 |
+
"90%": 10100.2,
|
| 156 |
+
"99%": 38764.44,
|
| 157 |
+
"max": 55414.0
|
| 158 |
+
},
|
| 159 |
+
"output_tokens": {
|
| 160 |
+
"mean": 78.284853,
|
| 161 |
+
"std": 169.967905,
|
| 162 |
+
"min": 1.0,
|
| 163 |
+
"25%": 33.0,
|
| 164 |
+
"50%": 52.0,
|
| 165 |
+
"75%": 88.0,
|
| 166 |
+
"90%": 143.0,
|
| 167 |
+
"99%": 337.44,
|
| 168 |
+
"max": 4105.0
|
| 169 |
+
},
|
| 170 |
+
"total_tokens": {
|
| 171 |
+
"mean": 6932.600765,
|
| 172 |
+
"std": 5547.844673,
|
| 173 |
+
"min": 244.0,
|
| 174 |
+
"25%": 4796.0,
|
| 175 |
+
"50%": 7082.0,
|
| 176 |
+
"75%": 8765.0,
|
| 177 |
+
"90%": 10172.2,
|
| 178 |
+
"99%": 38824.04,
|
| 179 |
+
"max": 55553.0
|
| 180 |
+
},
|
| 181 |
+
"total_input_tokens": 59145892,
|
| 182 |
+
"total_output_tokens": 675520,
|
| 183 |
+
"total_tokens_count": 59821412
|
| 184 |
+
}
|
| 185 |
+
}
|
| 186 |
+
},
|
| 187 |
+
"num": 2190
|
| 188 |
+
}
|