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Copy pathtrain.sdk.evalset.json
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70 lines (70 loc) · 1.84 KB
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{
"eval_set_id": "plate_agent_train",
"name": "PlateAgent 璁粌闆?- 杞︾墝璇嗗埆",
"description": "3 寮犱唬琛ㄦ€ц溅鐗屽浘鍍忥紝瑕嗙洊娓呮櫚/鍣0/妯$硦涓夌鍦烘櫙锛岀敤浜嶨EPA 鍙嶆€濅紭鍖栨椂鐨?mini-batch",
"eval_cases": [
{
"eval_id": "train_clear_001",
"conversation": [
{
"invocation_id": "t1",
"user_content": {
"parts": [{"text": "璇嗗埆杩欏紶杞︾墝: image: plate_001.jpg"}],
"role": "user"
},
"final_response": {
"parts": [{"text": "浜珹12345"}],
"role": "model"
}
}
],
"session_input": {
"app_name": "plate_optimizer",
"user_id": "trainer",
"state": {}
}
},
{
"eval_id": "train_noise_002",
"conversation": [
{
"invocation_id": "t2",
"user_content": {
"parts": [{"text": "璇嗗埆杩欏紶杞︾墝: image: plate_028.jpg"}],
"role": "user"
},
"final_response": {
"parts": [{"text": "浜珹12345"}],
"role": "model"
}
}
],
"session_input": {
"app_name": "plate_optimizer",
"user_id": "trainer",
"state": {}
}
},
{
"eval_id": "train_blur_003",
"conversation": [
{
"invocation_id": "t3",
"user_content": {
"parts": [{"text": "璇嗗埆杩欏紶杞︾墝: image: plate_012.jpg"}],
"role": "user"
},
"final_response": {
"parts": [{"text": "鑻廥8U88"}],
"role": "model"
}
}
],
"session_input": {
"app_name": "plate_optimizer",
"user_id": "trainer",
"state": {}
}
}
]
}