Remove old version evals results (1.0.0)

.gitignore

@@ -0,0 +1,3 @@
+.ipynb_checkpoints
+*/.ipynb_checkpoints/*
+

01-ai/Yi-34B-200K_eval_request_False_bfloat16_Original.json

@@ -13,18 +13,6 @@
     "source": "script",
     "job_id": 253,
     "job_start_time": "2024-02-21T12-10-33.914064",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.7186843946815955,
-        "bluex": 0.6634214186369958,
-        "oab_exams": 0.571753986332574,
-        "assin2_rte": 0.7858403678133732,
-        "assin2_sts": 0.5583683246827316,
-        "faquad_nli": 0.7800338409475465,
-        "sparrow_pt": 0.37142261482383704
-    },
-    "result_metrics_average": 0.6356464211312362,
-    "result_metrics_npm": 0.4967380342980293,
     "error_msg": "CUDA out of memory. Tried to allocate 298.02 GiB. GPU 0 has a total capacty of 79.35 GiB of which 14.77 GiB is free. Process 580799 has 64.57 GiB memory in use. Of the allocated memory 64.06 GiB is allocated by PyTorch, and 7.19 MiB 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 191, 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 100, in simple_evaluate\n    lm = lm_eval.api.registry.get_model(model).create_from_arg_string(\n         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/api/model.py\", line 134, in create_from_arg_string\n    return cls(**args, **args2)\n           ^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/models/huggingface.py\", line 293, in __init__\n    self._create_model(\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/models/huggingface.py\", line 604, in _create_model\n    self._model = self.AUTO_MODEL_CLASS.from_pretrained(\n                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py\", line 561, in from_pretrained\n    return model_class.from_pretrained(\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 3558, in from_pretrained\n    dispatch_model(model, **device_map_kwargs)\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/accelerate/big_modeling.py\", line 445, in dispatch_model\n    model.to(device)\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 2556, in to\n    return super().to(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1160, in to\n    return self._apply(convert)\n           ^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 810, in _apply\n    module._apply(fn)\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 857, in _apply\n    self._buffers[key] = fn(buf)\n                         ^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1158, in convert\n    return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\ntorch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 298.02 GiB. GPU 0 has a total capacty of 79.35 GiB of which 14.77 GiB is free. Process 580799 has 64.57 GiB memory in use. Of the allocated memory 64.06 GiB is allocated by PyTorch, and 7.19 MiB 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"
 }

01-ai/Yi-34B_eval_request_False_bfloat16_Original.json

@@ -13,18 +13,6 @@
     "source": "script",
     "job_id": 281,
     "job_start_time": "2024-02-28T16-27-11.805205",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.7214835549335199,
-        "bluex": 0.6842837273991655,
-        "oab_exams": 0.566742596810934,
-        "assin2_rte": 0.7095337812960236,
-        "assin2_sts": 0.6212032386293976,
-        "faquad_nli": 0.7969022005981341,
-        "sparrow_pt": 0.3916234220734354
-    },
-    "result_metrics_average": 0.6416817888200871,
-    "result_metrics_npm": 0.4958265468665359,
     "error_msg": "CUDA out of memory. Tried to allocate 98.00 MiB. GPU 0 has a total capacty of 79.35 GiB of which 96.19 MiB is free. Process 1027082 has 63.32 GiB memory in use. Process 2746447 has 9.96 GiB memory in use. Process 3815607 has 3.34 GiB memory in use. Process 3812636 has 2.60 GiB memory in use. Process 3812253 has 73.00 MiB memory in use. Of the allocated memory 62.82 GiB is allocated by PyTorch, and 396.00 KiB 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 207, 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 100, in simple_evaluate\n    lm = lm_eval.api.registry.get_model(model).create_from_arg_string(\n         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/api/model.py\", line 134, in create_from_arg_string\n    return cls(**args, **args2)\n           ^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/models/huggingface.py\", line 293, in __init__\n    self._create_model(\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/models/huggingface.py\", line 604, in _create_model\n    self._model = self.AUTO_MODEL_CLASS.from_pretrained(\n                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py\", line 561, in from_pretrained\n    return model_class.from_pretrained(\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 3502, in from_pretrained\n    ) = cls._load_pretrained_model(\n        ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 3926, in _load_pretrained_model\n    new_error_msgs, offload_index, state_dict_index = _load_state_dict_into_meta_model(\n                                                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 805, in _load_state_dict_into_meta_model\n    set_module_tensor_to_device(model, param_name, param_device, **set_module_kwargs)\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/accelerate/utils/modeling.py\", line 347, in set_module_tensor_to_device\n    new_value = value.to(device)\n                ^^^^^^^^^^^^^^^^\ntorch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 98.00 MiB. GPU 0 has a total capacty of 79.35 GiB of which 96.19 MiB is free. Process 1027082 has 63.32 GiB memory in use. Process 2746447 has 9.96 GiB memory in use. Process 3815607 has 3.34 GiB memory in use. Process 3812636 has 2.60 GiB memory in use. Process 3812253 has 73.00 MiB memory in use. Of the allocated memory 62.82 GiB is allocated by PyTorch, and 396.00 KiB 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"
 }

01-ai/Yi-6B-200K_eval_request_False_bfloat16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 121,
-    "job_start_time": "2024-02-09T07-10-30.923872",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.5703289013296011,
-        "bluex": 0.49791376912378305,
-        "oab_exams": 0.4419134396355353,
-        "assin2_rte": 0.7574463542222696,
-        "assin2_sts": 0.3059276997249324,
-        "faquad_nli": 0.4471267110923455,
-        "sparrow_pt": 0.31180320008181783
-    },
-    "result_metrics_average": 0.47606572503004063,
-    "result_metrics_npm": 0.2713265790562599
+    "job_start_time": "2024-02-09T07-10-30.923872"
 }

22h/cabrita_7b_pt_850000_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🆎 : language adapted models (FP, FT, ...)",
     "source": "script",
     "job_id": 213,
-    "job_start_time": "2024-02-16T13-19-48.657595",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.2218334499650105,
-        "bluex": 0.24895688456189152,
-        "oab_exams": 0.2783599088838269,
-        "assin2_rte": 0.6996743545023234,
-        "assin2_sts": 0.007646758869425693,
-        "faquad_nli": 0.17721518987341772,
-        "sparrow_pt": 0.26278701409945776
-    },
-    "result_metrics_average": 0.27092479439362194,
-    "result_metrics_npm": -0.00787880781904908
+    "job_start_time": "2024-02-16T13-19-48.657595"
 }

AI-Sweden-Models/gpt-sw3-20b_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 102,
-    "job_start_time": "2024-02-08T16-32-05.080295",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.19454163750874737,
-        "bluex": 0.21835883171070933,
-        "oab_exams": 0.24009111617312073,
-        "assin2_rte": 0.5097556100727492,
-        "assin2_sts": 0.04176979032426292,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.2261793330522781
-    },
-    "result_metrics_average": 0.2671930701793801,
-    "result_metrics_npm": -0.013569520485616151
+    "job_start_time": "2024-02-08T16-32-05.080295"
 }

AI-Sweden-Models/gpt-sw3-6.7b-v2_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 101,
-    "job_start_time": "2024-02-08T15-37-30.575084",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.2344296710986704,
-        "bluex": 0.2086230876216968,
-        "oab_exams": 0.23006833712984054,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.015469193291869708,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.21165120316324165
-    },
-    "result_metrics_average": 0.2390328568646351,
-    "result_metrics_npm": -0.06725785488427993
+    "job_start_time": "2024-02-08T15-37-30.575084"
 }

AI-Sweden-Models/gpt-sw3-6.7b_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 100,
-    "job_start_time": "2024-02-08T14-27-00.255851",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.20363890832750176,
-        "bluex": 0.24478442280945759,
-        "oab_exams": 0.23006833712984054,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.018735799862626468,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.19168746791328134
-    },
-    "result_metrics_average": 0.23741477739854774,
-    "result_metrics_npm": -0.06966919981551431
+    "job_start_time": "2024-02-08T14-27-00.255851"
 }

BAAI/Aquila-7B_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 182,
-    "job_start_time": "2024-02-13T21-53-04.495865",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.3002099370188943,
-        "bluex": 0.29763560500695413,
-        "oab_exams": 0.2988610478359909,
-        "assin2_rte": 0.48191507425133256,
-        "assin2_sts": 0.2947702523754177,
-        "faquad_nli": 0.47700641417918904,
-        "sparrow_pt": 0.2413705187861493
-    },
-    "result_metrics_average": 0.341681264207704,
-    "result_metrics_npm": 0.07218268472291701
+    "job_start_time": "2024-02-13T21-53-04.495865"
 }

BAAI/Aquila2-34B_eval_request_False_bfloat16_Original.json

@@ -13,18 +13,6 @@
     "source": "script",
     "job_id": 253,
     "job_start_time": "2024-02-20T17-38-24.783283",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.543037088873338,
-        "bluex": 0.4297635605006954,
-        "oab_exams": 0.3981776765375854,
-        "assin2_rte": 0.7334164728077959,
-        "assin2_sts": 0.4958376987221018,
-        "faquad_nli": 0.45449901481427424,
-        "sparrow_pt": 0.3121381894628628
-    },
-    "result_metrics_average": 0.48098138595980766,
-    "result_metrics_npm": 0.26782837303937407,
     "error_msg": "Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!",
     "traceback": "Traceback (most recent call last):\n  File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/evaluate_llms.py\", line 191, 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 1513, 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 1058, 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 1524, in generate\n    return self.greedy_search(\n           ^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/generation/utils.py\", line 2361, in greedy_search\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/accelerate/hooks.py\", line 165, in new_forward\n    output = module._old_forward(*args, **kwargs)\n             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/models/llama/modeling_llama.py\", line 1148, 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 964, in forward\n    causal_mask = self._update_causal_mask(attention_mask, inputs_embeds)\n                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/models/llama/modeling_llama.py\", line 1055, in _update_causal_mask\n    padding_mask = causal_mask[..., :mask_length].eq(0.0) * attention_mask[:, None, None, :].eq(0.0)\n                   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\nRuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!\n"
 }

BAAI/Aquila2-7B_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 183,
-    "job_start_time": "2024-02-13T23-17-21.976390",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.2470258922323303,
-        "bluex": 0.20445062586926285,
-        "oab_exams": 0.2874715261958998,
-        "assin2_rte": 0.5642307632772472,
-        "assin2_sts": 0.32002670516594683,
-        "faquad_nli": 0.46611451506525536,
-        "sparrow_pt": 0.2587475557591692
-    },
-    "result_metrics_average": 0.3354382262235873,
-    "result_metrics_npm": 0.07112689461870844
+    "job_start_time": "2024-02-13T23-17-21.976390"
 }

DAMO-NLP-MT/polylm-1.7b_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 215,
-    "job_start_time": "2024-02-16T14-47-24.223296",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.19244226731980407,
-        "bluex": 0.24200278164116829,
-        "oab_exams": 0.24646924829157174,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.004714541859212106,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.23356086755006158
-    },
-    "result_metrics_average": 0.24173974462984918,
-    "result_metrics_npm": -0.0625754139616488
+    "job_start_time": "2024-02-16T14-47-24.223296"
 }

Deci/DeciLM-7B_eval_request_False_bfloat16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🔶 : fine-tuned",
     "source": "script",
     "job_id": 39,
-    "job_start_time": "2024-02-07T06-30-45.967063",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.529741077676697,
-        "bluex": 0.41168289290681503,
-        "oab_exams": 0.3990888382687927,
-        "assin2_rte": 0.7470003950561543,
-        "assin2_sts": 0.5145659724171266,
-        "faquad_nli": 0.7851487912814374,
-        "sparrow_pt": 0.3532299102024751
-    },
-    "result_metrics_average": 0.5343511254013569,
-    "result_metrics_npm": 0.3640082745590046
+    "job_start_time": "2024-02-07T06-30-45.967063"
 }

EleutherAI/gpt-j-6b_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 77,
-    "job_start_time": "2024-02-07T15-56-06.233510",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.21903428971308608,
-        "bluex": 0.19749652294853964,
-        "oab_exams": 0.24419134396355352,
-        "assin2_rte": 0.3512359875045344,
-        "assin2_sts": 0.09337260889279221,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.19440498214886542
-    },
-    "result_metrics_average": 0.24848441536930918,
-    "result_metrics_npm": -0.05661848481231452
+    "job_start_time": "2024-02-07T15-56-06.233510"
 }

EleutherAI/gpt-neo-1.3B_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 201,
-    "job_start_time": "2024-02-14T20-42-35.885763",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.19034289713086075,
-        "bluex": 0.20445062586926285,
-        "oab_exams": 0.23462414578587698,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.0070782273697892,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.24161040553185745
-    },
-    "result_metrics_average": 0.23587068677639625,
-    "result_metrics_npm": -0.07015978644825559
+    "job_start_time": "2024-02-14T20-42-35.885763"
 }

EleutherAI/gpt-neo-125m_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 200,
-    "job_start_time": "2024-02-14T20-18-41.235422",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.18964310706787962,
-        "bluex": 0.17524339360222532,
-        "oab_exams": 0.010933940774487472,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.10713084465982439,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.171051914297268
-    },
-    "result_metrics_average": 0.20385595802125872,
-    "result_metrics_npm": -0.11828056424440532
+    "job_start_time": "2024-02-14T20-18-41.235422"
 }

EleutherAI/gpt-neo-2.7B_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 202,
-    "job_start_time": "2024-02-14T21-23-17.848186",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.1952414275717285,
-        "bluex": 0.19193324061196107,
-        "oab_exams": 0.23234624145785876,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.006388450736995319,
-        "faquad_nli": 0.42535491344201753,
-        "sparrow_pt": 0.26425572526209995
-    },
-    "result_metrics_average": 0.2355504760594278,
-    "result_metrics_npm": -0.0712914298859
+    "job_start_time": "2024-02-14T21-23-17.848186"
 }

EleutherAI/gpt-neox-20b_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 78,
-    "job_start_time": "2024-02-07T16-49-06.259210",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.20083974807557733,
-        "bluex": 0.22531293463143254,
-        "oab_exams": 0.2560364464692483,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.1133653560992191,
-        "faquad_nli": 0.4718588278919615,
-        "sparrow_pt": 0.16031340502399352
-    },
-    "result_metrics_average": 0.2515800073606808,
-    "result_metrics_npm": -0.053194066948652974
+    "job_start_time": "2024-02-07T16-49-06.259210"
 }

EleutherAI/polyglot-ko-12.8b_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 203,
-    "job_start_time": "2024-02-14T22-19-56.698691",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.06717984604618614,
-        "bluex": 0.05285118219749652,
-        "oab_exams": 0.2355353075170843,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.019117347817184663,
-        "faquad_nli": 0.33515801835418463,
-        "sparrow_pt": 0.2154843220889051
-    },
-    "result_metrics_average": 0.17980847962205354,
-    "result_metrics_npm": -0.15093987610503895
+    "job_start_time": "2024-02-14T22-19-56.698691"
 }

EleutherAI/pythia-12b-deduped_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 199,
-    "job_start_time": "2024-02-14T18-51-32.259622",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.1973407977606718,
-        "bluex": 0.22809457579972184,
-        "oab_exams": 0.23599088838268792,
-        "assin2_rte": 0.33424046164366045,
-        "assin2_sts": 0.062042189457896954,
-        "faquad_nli": 0.43771626297577854,
-        "sparrow_pt": 0.23859602003664446
-    },
-    "result_metrics_average": 0.24771731372243738,
-    "result_metrics_npm": -0.05730030865088216
+    "job_start_time": "2024-02-14T18-51-32.259622"
 }

EleutherAI/pythia-14m_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 192,
-    "job_start_time": "2024-02-14T15-03-57.922027",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.0,
-        "bluex": 0.0,
-        "oab_exams": 0.0,
-        "assin2_rte": 0.0,
-        "assin2_sts": NaN,
-        "faquad_nli": 0.0,
-        "sparrow_pt": 0.0
-    },
-    "result_metrics_average": NaN,
-    "result_metrics_npm": NaN
+    "job_start_time": "2024-02-14T15-03-57.922027"
 }

EleutherAI/pythia-160m-deduped_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 194,
-    "job_start_time": "2024-02-14T15-27-43.932506",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.0,
-        "bluex": 0.0,
-        "oab_exams": 0.0,
-        "assin2_rte": 0.0,
-        "assin2_sts": NaN,
-        "faquad_nli": 0.0,
-        "sparrow_pt": 0.0
-    },
-    "result_metrics_average": NaN,
-    "result_metrics_npm": NaN
+    "job_start_time": "2024-02-14T15-27-43.932506"
 }

EleutherAI/pythia-1b-deduped_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 196,
-    "job_start_time": "2024-02-14T16-20-18.432424",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.2106368089573128,
-        "bluex": 0.18776077885952713,
-        "oab_exams": 0.24145785876993167,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.015287790416728658,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.1527947965732252
-    },
-    "result_metrics_average": 0.225846648474836,
-    "result_metrics_npm": -0.08513497266217881
+    "job_start_time": "2024-02-14T16-20-18.432424"
 }

EleutherAI/pythia-2.8b-deduped_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 197,
-    "job_start_time": "2024-02-14T16-49-11.216028",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.20433869839048285,
-        "bluex": 0.23504867872044508,
-        "oab_exams": 0.23280182232346242,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.032750005063908794,
-        "faquad_nli": 0.17721518987341772,
-        "sparrow_pt": 0.2216627443828188
-    },
-    "result_metrics_average": 0.20530721029826696,
-    "result_metrics_npm": -0.13166019646895838
+    "job_start_time": "2024-02-14T16-49-11.216028"
 }

EleutherAI/pythia-410m-deduped_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 195,
-    "job_start_time": "2024-02-14T15-42-42.785588",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.1980405878236529,
-        "bluex": 0.1571627260083449,
-        "oab_exams": 0.23599088838268792,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.0393820346422743,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.16268055200707188
-    },
-    "result_metrics_average": 0.22374932780159407,
-    "result_metrics_npm": -0.08862059215156827
+    "job_start_time": "2024-02-14T15-42-42.785588"
 }

EleutherAI/pythia-6.9b-deduped_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 198,
-    "job_start_time": "2024-02-14T17-44-29.767283",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.20503848845346395,
-        "bluex": 0.21835883171070933,
-        "oab_exams": 0.2669703872437358,
-        "assin2_rte": 0.33514630774633175,
-        "assin2_sts": 0.015459703136524651,
-        "faquad_nli": 0.5032594590990455,
-        "sparrow_pt": 0.16024035452533222
-    },
-    "result_metrics_average": 0.24349621884502046,
-    "result_metrics_npm": -0.056880866402642415
+    "job_start_time": "2024-02-14T17-44-29.767283"
 }

EleutherAI/pythia-70m-deduped_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 193,
-    "job_start_time": "2024-02-14T15-15-51.530711",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.0,
-        "bluex": 0.0,
-        "oab_exams": 0.0,
-        "assin2_rte": 0.0,
-        "assin2_sts": NaN,
-        "faquad_nli": 0.0,
-        "sparrow_pt": 0.0
-    },
-    "result_metrics_average": NaN,
-    "result_metrics_npm": NaN
+    "job_start_time": "2024-02-14T15-15-51.530711"
 }

HeyLucasLeao/gpt-neo-small-portuguese_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🆎 : language adapted models (FP, FT, ...)",
     "source": "script",
     "job_id": 93,
-    "job_start_time": "2024-02-08T01-23-52.798469",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.16235129461161651,
-        "bluex": 0.11265646731571627,
-        "oab_exams": 0.008656036446469248,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.04753851053349196,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.17064375718073424
-    },
-    "result_metrics_average": 0.18211922454787924,
-    "result_metrics_npm": -0.14372064652620473
+    "job_start_time": "2024-02-08T01-23-52.798469"
 }

NucleusAI/nucleus-22B-token-500B_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 191,
-    "job_start_time": "2024-02-14T13-14-20.585602",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.2232330300909727,
-        "bluex": 0.1808066759388039,
-        "oab_exams": 0.269248291571754,
-        "assin2_rte": 0.33965642015109887,
-        "assin2_sts": 0.14105865232500697,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.14936340466616818
-    },
-    "result_metrics_average": 0.2490030924510854,
-    "result_metrics_npm": -0.05979554926598268
+    "job_start_time": "2024-02-14T13-14-20.585602"
 }

OpenLLM-France/Claire-7B-0.1_eval_request_False_bfloat16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🆎 : language adapted models (FP, FT, ...)",
     "source": "script",
     "job_id": 105,
-    "job_start_time": "2024-02-08T19-59-33.207703",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.21203638908327502,
-        "bluex": 0.24617524339360222,
-        "oab_exams": 0.24738041002277905,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.043451880521346076,
-        "faquad_nli": 0.4471267110923455,
-        "sparrow_pt": 0.2339910645108228
-    },
-    "result_metrics_average": 0.25192786170821485,
-    "result_metrics_npm": -0.05055064976935545
+    "job_start_time": "2024-02-08T19-59-33.207703"
 }

OpenLLM-France/Claire-Mistral-7B-0.1_eval_request_False_bfloat16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🆎 : language adapted models (FP, FT, ...)",
     "source": "script",
     "job_id": 104,
-    "job_start_time": "2024-02-08T18-48-18.223603",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.5864240727781665,
-        "bluex": 0.4603616133518776,
-        "oab_exams": 0.41275626423690204,
-        "assin2_rte": 0.3930811717227137,
-        "assin2_sts": 0.5428546315437224,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.26612905967383516
-    },
-    "result_metrics_average": 0.4430374265315729,
-    "result_metrics_npm": 0.18025007075022711
+    "job_start_time": "2024-02-08T18-48-18.223603"
 }

OrionStarAI/Orion-14B-Base_eval_request_False_bfloat16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 179,
-    "job_start_time": "2024-02-13T19-40-35.556453",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.6627011896431071,
-        "bluex": 0.5702364394993046,
-        "oab_exams": 0.47289293849658315,
-        "assin2_rte": 0.6307200282684031,
-        "assin2_sts": 0.5853055022861218,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.32190683171450984
-    },
-    "result_metrics_average": 0.5262025860459747,
-    "result_metrics_npm": 0.3108427262693092
+    "job_start_time": "2024-02-13T19-40-35.556453"
 }

Skywork/Skywork-13B-base_eval_request_False_bfloat16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 176,
-    "job_start_time": "2024-02-13T13-13-14.633268",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.6242127361791463,
-        "bluex": 0.4937413073713491,
-        "oab_exams": 0.4104783599088838,
-        "assin2_rte": 0.6640797445169774,
-        "assin2_sts": 0.109966284351211,
-        "faquad_nli": 0.5733609182848322,
-        "sparrow_pt": 0.337302679211532
-    },
-    "result_metrics_average": 0.45902028997484745,
-    "result_metrics_npm": 0.25783808569270167
+    "job_start_time": "2024-02-13T13-13-14.633268"
 }

THUDM/chatglm3-6b-base_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 184,
-    "job_start_time": "2024-02-14T00-29-11.353268",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.6081175647305809,
-        "bluex": 0.49235048678720444,
-        "oab_exams": 0.40501138952164006,
-        "assin2_rte": 0.6004172619619615,
-        "assin2_sts": 0.7205871294107395,
-        "faquad_nli": 0.8115869651008071,
-        "sparrow_pt": 0.37512447333212245
-    },
-    "result_metrics_average": 0.5733136101207224,
-    "result_metrics_npm": 0.39293186808439523
+    "job_start_time": "2024-02-14T00-29-11.353268"
 }

baichuan-inc/Baichuan-7B_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 176,
-    "job_start_time": "2024-02-13T16-00-29.790614",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.20573827851644508,
-        "bluex": 0.20584144645340752,
-        "oab_exams": 0.23690205011389523,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.16664859797501688,
-        "faquad_nli": 0.41377140792945644,
-        "sparrow_pt": 0.25291474912683454
-    },
-    "result_metrics_average": 0.25930712334976985,
-    "result_metrics_npm": -0.048431144903189324
+    "job_start_time": "2024-02-13T16-00-29.790614"
 }

baichuan-inc/Baichuan2-13B-Base_eval_request_False_bfloat16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 178,
-    "job_start_time": "2024-02-13T18-20-08.619292",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.37788663400979705,
-        "bluex": 0.3129346314325452,
-        "oab_exams": 0.34943052391799545,
-        "assin2_rte": 0.5360021760870939,
-        "assin2_sts": 0.1052548005298192,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.2957930022375439
-    },
-    "result_metrics_average": 0.34527956294694107,
-    "result_metrics_npm": 0.08810495779838001
+    "job_start_time": "2024-02-13T18-20-08.619292"
 }

baichuan-inc/Baichuan2-7B-Base_eval_request_False_bfloat16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 177,
-    "job_start_time": "2024-02-13T18-20-08.619747",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.4989503149055283,
-        "bluex": 0.4019471488178025,
-        "oab_exams": 0.371753986332574,
-        "assin2_rte": 0.5418181818181818,
-        "assin2_sts": 0.18098885021409325,
-        "faquad_nli": 0.45391686964720673,
-        "sparrow_pt": 0.24948648514446742
-    },
-    "result_metrics_average": 0.3855516909828363,
-    "result_metrics_npm": 0.137226170969913
+    "job_start_time": "2024-02-13T18-20-08.619747"
 }

bigscience/bloom-3b_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 27,
-    "job_start_time": "2024-02-07T01-42-50.987972",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.2001399580125962,
-        "bluex": 0.18776077885952713,
-        "oab_exams": 0.25740318906605925,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.007784203462752267,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.16983005721811856
-    },
-    "result_metrics_average": 0.2279866703380257,
-    "result_metrics_npm": -0.08159221837126322
+    "job_start_time": "2024-02-07T01-42-50.987972"
 }

deepseek-ai/deepseek-llm-67b-base_eval_request_False_bfloat16_Original.json

@@ -13,18 +13,6 @@
     "source": "script",
     "job_id": 253,
     "job_start_time": "2024-02-20T17-31-20.642276",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.7333799860041987,
-        "bluex": 0.6244784422809457,
-        "oab_exams": 0.532118451025057,
-        "assin2_rte": 0.6950181531654831,
-        "assin2_sts": 0.5337084187331966,
-        "faquad_nli": 0.6754332808144468,
-        "sparrow_pt": 0.36690087459679466
-    },
-    "result_metrics_average": 0.5944339438028746,
-    "result_metrics_npm": 0.4267772506411939,
     "error_msg": "Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!",
     "traceback": "Traceback (most recent call last):\n  File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/evaluate_llms.py\", line 191, 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 1513, 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 1058, 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 1524, in generate\n    return self.greedy_search(\n           ^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/generation/utils.py\", line 2361, in greedy_search\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/accelerate/hooks.py\", line 165, in new_forward\n    output = module._old_forward(*args, **kwargs)\n             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/models/llama/modeling_llama.py\", line 1148, 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 964, in forward\n    causal_mask = self._update_causal_mask(attention_mask, inputs_embeds)\n                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/models/llama/modeling_llama.py\", line 1055, in _update_causal_mask\n    padding_mask = causal_mask[..., :mask_length].eq(0.0) * attention_mask[:, None, None, :].eq(0.0)\n                   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\nRuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!\n"
 }

deepseek-ai/deepseek-llm-7b-base_eval_request_False_bfloat16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 180,
-    "job_start_time": "2024-02-13T20-08-54.493662",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.4086773967809657,
-        "bluex": 0.3908205841446453,
-        "oab_exams": 0.35353075170842824,
-        "assin2_rte": 0.36087257670772555,
-        "assin2_sts": 0.3246306803889829,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.3046492630055339
-    },
-    "result_metrics_average": 0.3689766321642964,
-    "result_metrics_npm": 0.0918381264358727
+    "job_start_time": "2024-02-13T20-08-54.493662"
 }

deepseek-ai/deepseek-moe-16b-base_eval_request_False_bfloat16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 181,
-    "job_start_time": "2024-02-13T21-07-50.712249",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.36599020293911827,
-        "bluex": 0.3087621696801113,
-        "oab_exams": 0.3316628701594533,
-        "assin2_rte": 0.3669298673297707,
-        "assin2_sts": 0.2023483280938947,
-        "faquad_nli": 0.45391686964720673,
-        "sparrow_pt": 0.24294255630381092
-    },
-    "result_metrics_average": 0.32465040916476656,
-    "result_metrics_npm": 0.0404271761205112
+    "job_start_time": "2024-02-13T21-07-50.712249"
 }

facebook/opt-1.3b_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 81,
-    "job_start_time": "2024-02-07T17-55-47.448141",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.20643806857942618,
-        "bluex": 0.20305980528511822,
-        "oab_exams": 0.2296127562642369,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.014294092039832406,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.23645916821985138
-    },
-    "result_metrics_average": 0.2375503423050845,
-    "result_metrics_npm": -0.06850955080705787
+    "job_start_time": "2024-02-07T17-55-47.448141"
 }

facebook/opt-125m_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 79,
-    "job_start_time": "2024-02-07T17-00-47.502507",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.20363890832750176,
-        "bluex": 0.18219749652294853,
-        "oab_exams": 0.0009111617312072893,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.045915967954967385,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.16100858918916303
-    },
-    "result_metrics_average": 0.19523723278184493,
-    "result_metrics_npm": -0.12718865648894817
+    "job_start_time": "2024-02-07T17-00-47.502507"
 }

facebook/opt-13b_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 84,
-    "job_start_time": "2024-02-07T19-29-22.779324",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.18964310706787962,
-        "bluex": 0.20584144645340752,
-        "oab_exams": 0.23416856492027335,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.013938417309944717,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.18566533417845207
-    },
-    "result_metrics_average": 0.22889219652529766,
-    "result_metrics_npm": -0.08047151398067605
+    "job_start_time": "2024-02-07T19-29-22.779324"
 }

facebook/opt-2.7b_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 82,
-    "job_start_time": "2024-02-07T18-37-10.420552",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.19384184744576627,
-        "bluex": 0.19193324061196107,
-        "oab_exams": 0.2296127562642369,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.016315511418924157,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.2232283026501764
-    },
-    "result_metrics_average": 0.23256002344831303,
-    "result_metrics_npm": -0.07520210793362635
+    "job_start_time": "2024-02-07T18-37-10.420552"
 }

facebook/opt-350m_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 80,
-    "job_start_time": "2024-02-07T17-20-17.729922",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.20363890832750176,
-        "bluex": 0.13351877607788595,
-        "oab_exams": 0.00683371298405467,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.018818660102831564,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.2158151928608465
-    },
-    "result_metrics_average": 0.1930876794428924,
-    "result_metrics_npm": -0.12779893672772347
+    "job_start_time": "2024-02-07T17-20-17.729922"
 }

google/umt5-base_eval_request_False_bfloat16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 206,
-    "job_start_time": "2024-02-15T05-17-17.944550",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.02939118264520644,
-        "bluex": 0.022253129346314324,
-        "oab_exams": 0.08337129840546698,
-        "assin2_rte": 0.008049597487606372,
-        "assin2_sts": 0.11702145458274152,
-        "faquad_nli": 0.005177993527508091,
-        "sparrow_pt": 0.06908735918169881
-    },
-    "result_metrics_average": 0.04776457359664892,
-    "result_metrics_npm": -0.38758303220535195
+    "job_start_time": "2024-02-15T05-17-17.944550"
 }

google/umt5-small_eval_request_False_bfloat16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 205,
-    "job_start_time": "2024-02-15T02-03-26.881523",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.09447165850244926,
-        "bluex": 0.02642559109874826,
-        "oab_exams": 0.1489749430523918,
-        "assin2_rte": 0.19257980378257433,
-        "assin2_sts": 0.043458369255268595,
-        "faquad_nli": 0.014741228752745068,
-        "sparrow_pt": 0.011063279665311027
-    },
-    "result_metrics_average": 0.07595926772992691,
-    "result_metrics_npm": -0.32972887684471675
+    "job_start_time": "2024-02-15T02-03-26.881523"
 }

gpt2_eval_request_False_float16_Original.json

@@ -12,17 +12,5 @@
     "model_type": "🟢 : pretrained",
     "source": "script",
     "job_id": 187,
-    "job_start_time": "2024-02-14T01-24-06.058943",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.1364590622813156,
-        "bluex": 0.1933240611961057,
-        "oab_exams": 0.21685649202733484,
-        "assin2_rte": 0.3333333333333333,
-        "assin2_sts": 0.039726178664430394,
-        "faquad_nli": 0.4396551724137931,
-        "sparrow_pt": 0.1782807939159107
-    },
-    "result_metrics_average": 0.21966215626174623,
-    "result_metrics_npm": -0.09338594948484692
+    "job_start_time": "2024-02-14T01-24-06.058943"
 }

huggyllama/llama-30b_eval_request_False_float16_Original.json

@@ -13,18 +13,6 @@
     "source": "script",
     "job_id": 253,
     "job_start_time": "2024-02-21T12-12-04.504997",
-    "eval_version": "1.0.0",
-    "result_metrics": {
-        "enem_challenge": 0.6186144156752974,
-        "bluex": 0.5034770514603616,
-        "oab_exams": 0.4214123006833713,
-        "assin2_rte": 0.6994823029869264,
-        "assin2_sts": 0.521939545377829,
-        "faquad_nli": 0.5100755946706865,
-        "sparrow_pt": 0.32914824721309877
-    },
-    "result_metrics_average": 0.514878494009653,
-    "result_metrics_npm": 0.3114125756635208,
     "error_msg": "Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!",
     "traceback": "Traceback (most recent call last):\n  File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/evaluate_llms.py\", line 191, 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 1513, 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 1058, 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 1524, in generate\n    return self.greedy_search(\n           ^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/generation/utils.py\", line 2361, in greedy_search\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/accelerate/hooks.py\", line 165, in new_forward\n    output = module._old_forward(*args, **kwargs)\n             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/models/llama/modeling_llama.py\", line 1148, 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 964, in forward\n    causal_mask = self._update_causal_mask(attention_mask, inputs_embeds)\n                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/models/llama/modeling_llama.py\", line 1055, in _update_causal_mask\n    padding_mask = causal_mask[..., :mask_length].eq(0.0) * attention_mask[:, None, None, :].eq(0.0)\n                   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\nRuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!\n"
 }