Update status of WizardLM/WizardLM-13B-V1.2_eval_request_False_float16_Original to FAILED
d8a040d
verified
{ | |
"model": "WizardLM/WizardLM-13B-V1.2", | |
"base_model": "", | |
"revision": "main", | |
"private": false, | |
"precision": "float16", | |
"params": 13.0, | |
"architectures": "LlamaForCausalLM", | |
"weight_type": "Original", | |
"status": "FAILED", | |
"submitted_time": "2024-03-05T16:38:35Z", | |
"model_type": "💬 : chat models (RLHF, DPO, IFT, ...)", | |
"source": "leaderboard", | |
"job_id": 405, | |
"job_start_time": "2024-04-07T23-57-22.053764", | |
"main_language": "English", | |
"error_msg": "CUDA error: invalid resource handle\nCUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1.\nCompile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", | |
"traceback": "Traceback (most recent call last):\n File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/evaluate_llms.py\", line 190, in wait_download_and_run_request\n run_request(\n File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/evaluate_llms.py\", line 64, in run_request\n results = run_eval_on_model(\n ^^^^^^^^^^^^^^^^^^\n File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/run_eval.py\", line 55, in run_eval_on_model\n result = evaluate(\n ^^^^^^^^^\n File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/lm_eval_util.py\", line 145, in evaluate\n results = evaluator.simple_evaluate(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/utils.py\", line 415, in _wrapper\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/evaluator.py\", line 159, in simple_evaluate\n results = evaluate(\n ^^^^^^^^^\n File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/utils.py\", line 415, in _wrapper\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/evaluator.py\", line 343, in evaluate\n resps = getattr(lm, reqtype)(cloned_reqs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/models/huggingface.py\", line 1426, in generate_until\n batch_size, _ = self._detect_batch_size_and_length()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/models/huggingface.py\", line 815, in _detect_batch_size_and_length\n batch_size, max_length = forward_batch()\n ^^^^^^^^^^^^^^^\n File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/models/huggingface.py\", line 144, in decorator\n return function(batch_size, max_length, *args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/models/huggingface.py\", line 806, in forward_batch\n test_batch = torch.ones(\n ^^^^^^^^^^^\nRuntimeError: CUDA error: invalid resource handle\nCUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1.\nCompile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n\n" | |
} |