Update status of Xwin-LM/Xwin-LM-13B-V0.2_eval_request_False_float16_Original to FAILED

Xwin-LM/Xwin-LM-13B-V0.2_eval_request_False_float16_Original.json

@@ -8,10 +8,12 @@
     "architectures": "LlamaForCausalLM",
     "weight_type": "Original",
     "main_language": "English",
-    "status": "RUNNING",
+    "status": "FAILED",
     "submitted_time": "2024-05-22T01:13:35Z",
     "model_type": "💬 : chat (RLHF, DPO, IFT, ...)",
     "source": "leaderboard",
     "job_id": 740,
-    "job_start_time": "2024-05-26T00-38-56.863712"
+    "job_start_time": "2024-05-26T00-38-56.863712",
+    "error_msg": "CUDA out of memory. Tried to allocate 430.00 MiB. GPU 0 has a total capacty of 79.35 GiB of which 29.25 GiB is free. Process 1279938 has 492.00 MiB memory in use. Process 1295240 has 8.72 GiB memory in use. Process 412902 has 40.89 GiB memory in use. Of the allocated memory 35.41 GiB is allocated by PyTorch, and 4.02 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF",
+    "traceback": "Traceback (most recent call last):\n  File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/evaluate_llms.py\", line 198, in wait_download_and_run_request\n    run_request(\n  File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/evaluate_llms.py\", line 70, in run_request\n    results = run_eval_on_model(\n              ^^^^^^^^^^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/run_eval.py\", line 60, 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 419, 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 419, 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 1525, in generate_until\n    cont = self._model_generate(\n           ^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/models/huggingface.py\", line 1070, in _model_generate\n    return self.model.generate(\n           ^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/utils/_contextlib.py\", line 115, in decorate_context\n    return func(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/generation/utils.py\", line 1736, in generate\n    result = self._sample(\n             ^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/generation/utils.py\", line 2375, in _sample\n    outputs = self(\n              ^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1518, in _wrapped_call_impl\n    return self._call_impl(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1527, in _call_impl\n    return forward_call(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/models/llama/modeling_llama.py\", line 1164, in forward\n    outputs = self.model(\n              ^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1518, in _wrapped_call_impl\n    return self._call_impl(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1527, in _call_impl\n    return forward_call(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/models/llama/modeling_llama.py\", line 968, in forward\n    layer_outputs = decoder_layer(\n                    ^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1518, in _wrapped_call_impl\n    return self._call_impl(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1527, in _call_impl\n    return forward_call(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/models/llama/modeling_llama.py\", line 727, in forward\n    hidden_states = self.mlp(hidden_states)\n                    ^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1518, in _wrapped_call_impl\n    return self._call_impl(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1527, in _call_impl\n    return forward_call(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/models/llama/modeling_llama.py\", line 216, in forward\n    down_proj = self.down_proj(self.act_fn(self.gate_proj(x)) * self.up_proj(x))\n                               ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~\ntorch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 430.00 MiB. GPU 0 has a total capacty of 79.35 GiB of which 29.25 GiB is free. Process 1279938 has 492.00 MiB memory in use. Process 1295240 has 8.72 GiB memory in use. Process 412902 has 40.89 GiB memory in use. Of the allocated memory 35.41 GiB is allocated by PyTorch, and 4.02 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF\n"
 }