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ckpts/universal/global_step20/zero/5.mlp.dense_4h_to_h.weight/exp_avg_sq.pt

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lm-evaluation-harness/wandb/run-20240514_164521-zso8ava4/files/config.yaml

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lm-evaluation-harness/wandb/run-20240514_164521-zso8ava4/files/output.log

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+
+2024-05-14:16:45:22,362 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-14:16:45:26,887 INFO     [__main__.py:335] Selected Tasks: ['indiccopa-hi']
+2024-05-14:16:45:26,888 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-14:16:45:26,888 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/data/cronscript/ckpts//hf_ckpt//global_step120'}
+Traceback (most recent call last):
+  File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
+    return _run_code(code, main_globals, None,
+  File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
+    exec(code, run_globals)
+  File "/data/cronscript/lm-evaluation-harness/lm_eval/__main__.py", line 417, in <module>
+    cli_evaluate()
+  File "/data/cronscript/lm-evaluation-harness/lm_eval/__main__.py", line 341, in cli_evaluate
+    results = evaluator.simple_evaluate(
+  File "/data/cronscript/lm-evaluation-harness/lm_eval/utils.py", line 288, in _wrapper
+    return fn(*args, **kwargs)
+  File "/data/cronscript/lm-evaluation-harness/lm_eval/evaluator.py", line 180, in simple_evaluate
+    lm = lm_eval.api.registry.get_model(model).create_from_arg_string(
+  File "/data/cronscript/lm-evaluation-harness/lm_eval/api/model.py", line 134, in create_from_arg_string
+    return cls(**args, **args2)
+  File "/data/cronscript/lm-evaluation-harness/lm_eval/models/huggingface.py", line 190, in __init__
+    self._get_config(
+  File "/data/cronscript/lm-evaluation-harness/lm_eval/models/huggingface.py", line 471, in _get_config
+    self._config = transformers.AutoConfig.from_pretrained(
+  File "/usr/local/lib/python3.10/dist-packages/transformers/models/auto/configuration_auto.py", line 928, in from_pretrained
+    config_dict, unused_kwargs = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/transformers/configuration_utils.py", line 631, in get_config_dict
+    config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/transformers/configuration_utils.py", line 686, in _get_config_dict
+    resolved_config_file = cached_file(
+  File "/usr/local/lib/python3.10/dist-packages/transformers/utils/hub.py", line 369, in cached_file
+    raise EnvironmentError(
+OSError: /data/cronscript/ckpts//hf_ckpt//global_step120 does not appear to have a file named config.json. Checkout 'https://huggingface.co//data/cronscript/ckpts//hf_ckpt//global_step120/tree/main' for available files.

lm-evaluation-harness/wandb/run-20240514_164521-zso8ava4/files/requirements.txt

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+peft==0.10.0
+perfetto==0.7.0
+pip==22.0.2
+pip==23.3.1
+platformdirs==4.2.0
+pluggy==1.4.0
+portalocker==2.8.2
+pre-commit==3.3.3
+protobuf==3.20.3
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lm-evaluation-harness/wandb/run-20240514_164521-zso8ava4/logs/debug.log

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lm-evaluation-harness/wandb/run-20240523_123942-6rczgocn/files/config.yaml

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+_wandb:
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+    cli_version: 0.17.0
+    framework: huggingface
+    huggingface_version: 4.41.1
+    is_jupyter_run: false
+    is_kaggle_kernel: false
+    start_time: 1716467982
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lm-evaluation-harness/wandb/run-20240523_123942-6rczgocn/files/output.log

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+
+2024-05-23:12:39:43,445 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-23:12:39:51,992 INFO     [__main__.py:335] Selected Tasks: ['arc_easy', 'hellaswag', 'mrpc', 'openbookqa', 'sst2', 'winogrande']
+2024-05-23:12:39:51,993 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-23:12:39:51,993 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/mnt/weka/peacock/experiments/llama/checkpoint/llamav2-3b//hf_ckpt//global_step8000'}
+2024-05-23:12:39:54,299 INFO     [huggingface.py:164] Using device 'cuda'
+Traceback (most recent call last):
+  File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
+    return _run_code(code, main_globals, None,
+  File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
+    exec(code, run_globals)
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/__main__.py", line 417, in <module>
+    cli_evaluate()
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/__main__.py", line 341, in cli_evaluate
+    results = evaluator.simple_evaluate(
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/utils.py", line 288, in _wrapper
+    return fn(*args, **kwargs)
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/evaluator.py", line 180, in simple_evaluate
+    lm = lm_eval.api.registry.get_model(model).create_from_arg_string(
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/api/model.py", line 134, in create_from_arg_string
+    return cls(**args, **args2)
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/models/huggingface.py", line 190, in __init__
+    self._get_config(
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/models/huggingface.py", line 471, in _get_config
+    self._config = transformers.AutoConfig.from_pretrained(
+  File "/usr/local/lib/python3.10/dist-packages/transformers/models/auto/configuration_auto.py", line 934, in from_pretrained
+    config_dict, unused_kwargs = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/transformers/configuration_utils.py", line 632, in get_config_dict
+    config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/transformers/configuration_utils.py", line 689, in _get_config_dict
+    resolved_config_file = cached_file(
+  File "/usr/local/lib/python3.10/dist-packages/transformers/utils/hub.py", line 370, in cached_file
+    raise EnvironmentError(
+OSError: /mnt/weka/peacock/experiments/llama/checkpoint/llamav2-3b//hf_ckpt//global_step8000 does not appear to have a file named config.json. Checkout 'https://huggingface.co//mnt/weka/peacock/experiments/llama/checkpoint/llamav2-3b//hf_ckpt//global_step8000/tree/main' for available files.

lm-evaluation-harness/wandb/run-20240523_123942-6rczgocn/files/requirements.txt

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+GitPython==3.1.43
+Jinja2==3.1.4
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+evaluate==0.4.2
+exceptiongroup==1.2.1
+expecttest==0.2.1
+filelock==3.14.0
+frozenlist==1.4.1
+fsspec==2024.3.1
+gitdb==4.0.11
+google-auth-oauthlib==0.4.6
+google-auth==2.29.0
+grpcio==1.63.0
+habana-media-loader==1.15.1.15
+habana-pyhlml==1.15.1.15
+habana-torch-dataloader==1.15.1.15
+habana-torch-plugin==1.15.1.15
+habana_gpu_migration==1.15.1.15
+habana_quantization_toolkit==1.15.1.15
+hjson==3.1.0
+huggingface-hub==0.23.1
+identify==2.5.36
+idna==3.7
+iniconfig==2.0.0
+joblib==1.4.2
+jsonlines==4.0.0
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+lightning-utilities==0.11.2
+lightning==2.2.0.post0
+lm_eval==0.4.2
+lm_eval==0.4.2
+lm_eval==0.4.2
+lxml==5.2.2
+mbstrdecoder==1.1.3
+more-itertools==10.2.0
+mpi4py==3.1.4
+mpmath==1.3.0
+multidict==6.0.5
+multiprocess==0.70.16
+networkx==3.3
+ninja==1.11.1.1
+nltk==3.8.1
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+numexpr==2.10.0
+numpy==1.23.5
+oauthlib==3.2.2
+packaging==24.0
+pandas==2.0.1
+pathspec==0.12.1
+pathvalidate==3.2.0
+peft==0.11.1
+perfetto==0.7.0
+pillow==10.3.0
+pip==22.0.2
+pip==23.3.1
+platformdirs==4.2.1
+pluggy==1.5.0
+portalocker==2.8.2
+pre-commit==3.3.3
+pretty-errors==1.2.25
+protobuf==3.20.3
+psutil==5.9.8
+py-cpuinfo==9.0.0
+pyarrow-hotfix==0.6
+pyarrow==16.1.0
+pyasn1==0.6.0
+pyasn1_modules==0.4.0
+pybind11==2.10.4
+pycparser==2.22
+pydantic==1.10.13
+pynvml==8.0.4
+pytablewriter==1.2.0
+pytest==8.2.0
+python-dateutil==2.9.0.post0
+pytorch-lightning==2.2.4
+pytz==2024.1
+regex==2023.5.5
+requests-oauthlib==2.0.0
+requests==2.31.0
+rouge_score==0.1.2
+rsa==4.9
+sacrebleu==2.4.2
+safetensors==0.4.3
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+six==1.16.0
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+sympy==1.12
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+tcolorpy==0.1.6
+tdqm==0.0.1
+tensorboard-data-server==0.6.1
+tensorboard-plugin-wit==1.8.1
+tensorboard==2.11.2
+threadpoolctl==3.5.0
+tokenizers==0.19.1
+tomli==2.0.1
+torch==2.2.0a0+git8964477
+torch_tb_profiler==0.4.0
+torchaudio==2.2.0+08901ad
+torchdata==0.7.1+5e6f7b7
+torchmetrics==1.4.0
+torchtext==0.17.0+400da5c
+torchvision==0.17.0+b2383d4
+tqdm-multiprocess==0.0.11
+tqdm==4.66.4
+transformers==4.41.1
+typepy==1.3.2
+typing_extensions==4.11.0
+tzdata==2024.1
+urllib3==1.26.18
+virtualenv==20.26.1
+wandb==0.17.0
+wheel==0.37.1
+wheel==0.43.0
+word2number==1.1
+xxhash==3.4.1
+yamllint==1.35.1
+yarl==1.9.4
+zstandard==0.22.0

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lm-evaluation-harness/wandb/run-20240523_130853-oqhkxkfg/files/output.log

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+
+2024-05-23:13:08:54,324 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-23:13:09:02,773 INFO     [__main__.py:335] Selected Tasks: ['arc_easy', 'hellaswag', 'mrpc', 'openbookqa', 'sst2', 'winogrande']
+2024-05-23:13:09:02,774 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-23:13:09:02,775 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/mnt/weka/peacock/experiments/llama/checkpoint/llamav2-3b//hf_ckpt//global_step24000'}
+2024-05-23:13:09:05,069 INFO     [huggingface.py:164] Using device 'cuda'
+Traceback (most recent call last):
+  File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
+    return _run_code(code, main_globals, None,
+  File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
+    exec(code, run_globals)
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/__main__.py", line 417, in <module>
+    cli_evaluate()
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/__main__.py", line 341, in cli_evaluate
+    results = evaluator.simple_evaluate(
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/utils.py", line 288, in _wrapper
+    return fn(*args, **kwargs)
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/evaluator.py", line 180, in simple_evaluate
+    lm = lm_eval.api.registry.get_model(model).create_from_arg_string(
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/api/model.py", line 134, in create_from_arg_string
+    return cls(**args, **args2)
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/models/huggingface.py", line 190, in __init__
+    self._get_config(
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/models/huggingface.py", line 471, in _get_config
+    self._config = transformers.AutoConfig.from_pretrained(
+  File "/usr/local/lib/python3.10/dist-packages/transformers/models/auto/configuration_auto.py", line 934, in from_pretrained
+    config_dict, unused_kwargs = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/transformers/configuration_utils.py", line 632, in get_config_dict
+    config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/transformers/configuration_utils.py", line 689, in _get_config_dict
+    resolved_config_file = cached_file(
+  File "/usr/local/lib/python3.10/dist-packages/transformers/utils/hub.py", line 370, in cached_file
+    raise EnvironmentError(
+OSError: /mnt/weka/peacock/experiments/llama/checkpoint/llamav2-3b//hf_ckpt//global_step24000 does not appear to have a file named config.json. Checkout 'https://huggingface.co//mnt/weka/peacock/experiments/llama/checkpoint/llamav2-3b//hf_ckpt//global_step24000/tree/main' for available files.

lm-evaluation-harness/wandb/run-20240523_130853-oqhkxkfg/files/requirements.txt

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+evaluate==0.4.2
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+google-auth==2.29.0
+grpcio==1.63.0
+habana-media-loader==1.15.1.15
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+habana-torch-plugin==1.15.1.15
+habana_gpu_migration==1.15.1.15
+habana_quantization_toolkit==1.15.1.15
+hjson==3.1.0
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+identify==2.5.36
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+jsonlines==4.0.0
+lightning-habana==1.4.0
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+lightning==2.2.0.post0
+lm_eval==0.4.2
+lm_eval==0.4.2
+lm_eval==0.4.2
+lxml==5.2.2
+mbstrdecoder==1.1.3
+more-itertools==10.2.0
+mpi4py==3.1.4
+mpmath==1.3.0
+multidict==6.0.5
+multiprocess==0.70.16
+networkx==3.3
+ninja==1.11.1.1
+nltk==3.8.1
+nodeenv==1.8.0
+numexpr==2.10.0
+numpy==1.23.5
+oauthlib==3.2.2
+packaging==24.0
+pandas==2.0.1
+pathspec==0.12.1
+pathvalidate==3.2.0
+peft==0.11.1
+perfetto==0.7.0
+pillow==10.3.0
+pip==22.0.2
+pip==23.3.1
+platformdirs==4.2.1
+pluggy==1.5.0
+portalocker==2.8.2
+pre-commit==3.3.3
+pretty-errors==1.2.25
+protobuf==3.20.3
+psutil==5.9.8
+py-cpuinfo==9.0.0
+pyarrow-hotfix==0.6
+pyarrow==16.1.0
+pyasn1==0.6.0
+pyasn1_modules==0.4.0
+pybind11==2.10.4
+pycparser==2.22
+pydantic==1.10.13
+pynvml==8.0.4
+pytablewriter==1.2.0
+pytest==8.2.0
+python-dateutil==2.9.0.post0
+pytorch-lightning==2.2.4
+pytz==2024.1
+regex==2023.5.5
+requests-oauthlib==2.0.0
+requests==2.31.0
+rouge_score==0.1.2
+rsa==4.9
+sacrebleu==2.4.2
+safetensors==0.4.3
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+scipy==1.13.1
+sentencepiece==0.2.0
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+tensorboard-plugin-wit==1.8.1
+tensorboard==2.11.2
+threadpoolctl==3.5.0
+tokenizers==0.19.1
+tomli==2.0.1
+torch==2.2.0a0+git8964477
+torch_tb_profiler==0.4.0
+torchaudio==2.2.0+08901ad
+torchdata==0.7.1+5e6f7b7
+torchmetrics==1.4.0
+torchtext==0.17.0+400da5c
+torchvision==0.17.0+b2383d4
+tqdm-multiprocess==0.0.11
+tqdm==4.66.4
+transformers==4.41.1
+typepy==1.3.2
+typing_extensions==4.11.0
+tzdata==2024.1
+urllib3==1.26.18
+virtualenv==20.26.1
+wandb==0.17.0
+wheel==0.37.1
+wheel==0.43.0
+word2number==1.1
+xxhash==3.4.1
+yamllint==1.35.1
+yarl==1.9.4
+zstandard==0.22.0

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+2024-05-23 13:08:54,130 ERROR   HandlerThread:3128 [gitlib.py:root():92] git root error: Cmd('git') failed due to: exit code(128)
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+  value:
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+      group:
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+      dataset_path: allenai/ai2_arc
+      dataset_name: ARC-Easy
+      training_split: train
+      validation_split: validation
+      test_split: test
+      doc_to_text: 'Question: {{question}}
+
+        Answer:'
+      doc_to_target: '{{choices.label.index(answerKey)}}'
+      doc_to_choice: '{{choices.text}}'
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
+      num_fewshot: 0
+      metric_list:
+      - metric: acc
+        aggregation: mean
+        higher_is_better: true
+      - metric: acc_norm
+        aggregation: mean
+        higher_is_better: true
+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: true
+      doc_to_decontamination_query: 'Question: {{question}}
+
+        Answer:'
+      metadata:
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+    boolq:
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+      group:
+      - super-glue-lm-eval-v1
+      dataset_path: super_glue
+      dataset_name: boolq
+      training_split: train
+      validation_split: validation
+      doc_to_text: '{{passage}}
+
+        Question: {{question}}?
+
+        Answer:'
+      doc_to_target: label
+      doc_to_choice:
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+      - 'yes'
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
+      num_fewshot: 0
+      metric_list:
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+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: true
+      doc_to_decontamination_query: passage
+      metadata:
+        version: 2.0
+    copa:
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+      group:
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+      dataset_path: super_glue
+      dataset_name: copa
+      training_split: train
+      validation_split: validation
+      doc_to_text: "def doc_to_text(doc):\n    # Drop the period\n    connector =\
+        \ {\n        \"cause\": \"because\",\n        \"effect\": \"therefore\",\n\
+        \    }[doc[\"question\"]]\n    return doc[\"premise\"].strip()[:-1] + f\"\
+        \ {connector}\"\n"
+      doc_to_target: "def doc_to_target(doc):\n    correct_choice = doc[\"choice1\"\
+        ] if doc[\"label\"] == 0 else doc[\"choice2\"]\n    # Connect the sentences\n\
+        \    return \" \" + convert_choice(correct_choice)\n"
+      doc_to_choice: "def doc_to_choice(doc):\n    return [\" \" + convert_choice(doc[\"\
+        choice1\"]), \" \" + convert_choice(doc[\"choice2\"])]\n"
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
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+      metric_list:
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+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: false
+      metadata:
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+    mrpc:
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+      group: glue
+      dataset_path: glue
+      dataset_name: mrpc
+      training_split: train
+      validation_split: validation
+      doc_to_text: 'Sentence 1: {{sentence1}}
+
+        Sentence 2: {{sentence2}}
+
+        Question: Do both sentences mean the same thing?
+
+        Answer:'
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+      doc_to_choice:
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+      - 'yes'
+      description: ''
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+      fewshot_delimiter: '
+
+
+        '
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+      - metric: f1
+      output_type: multiple_choice
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+      should_decontaminate: false
+      metadata:
+        version: 1.0
+    piqa:
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+      dataset_path: piqa
+      training_split: train
+      validation_split: validation
+      doc_to_text: 'Question: {{goal}}
+
+        Answer:'
+      doc_to_target: label
+      doc_to_choice: '{{[sol1, sol2]}}'
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
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+
+        '
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+      metric_list:
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+      - metric: acc_norm
+        aggregation: mean
+        higher_is_better: true
+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: true
+      doc_to_decontamination_query: goal
+      metadata:
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+    sst2:
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+      group: glue
+      dataset_path: glue
+      dataset_name: sst2
+      training_split: train
+      validation_split: validation
+      doc_to_text: '{{sentence}}
+
+        Question: Is this sentence positive or negative?
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+        Answer:'
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+      doc_to_choice:
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+      - positive
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
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+      metric_list:
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+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: false
+      metadata:
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+    winogrande:
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+      dataset_path: winogrande
+      dataset_name: winogrande_xl
+      training_split: train
+      validation_split: validation
+      doc_to_text: "def doc_to_text(doc):\n    answer_to_num = {\"1\": 0, \"2\": 1}\n\
+        \    return answer_to_num[doc[\"answer\"]]\n"
+      doc_to_target: "def doc_to_target(doc):\n    idx = doc[\"sentence\"].index(\"\
+        _\") + 1\n    return doc[\"sentence\"][idx:].strip()\n"
+      doc_to_choice: "def doc_to_choice(doc):\n    idx = doc[\"sentence\"].index(\"\
+        _\")\n    options = [doc[\"option1\"], doc[\"option2\"]]\n    return [doc[\"\
+        sentence\"][:idx] + opt for opt in options]\n"
+      description: ''
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+      fewshot_delimiter: '
+
+
+        '
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+      metric_list:
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+        aggregation: mean
+        higher_is_better: true
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+      repeats: 1
+      should_decontaminate: true
+      doc_to_decontamination_query: sentence
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+  value:
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+    model_args: pretrained=/mnt/weka/peacock/experiments/llama/eval/checkpoint/llamav2-3b/hf/global_step40000,tokenizer=huggyllama/llama-13b
+    batch_size: auto
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+2024-05-29:13:05:48,442 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-29:13:05:57,979 INFO     [__main__.py:335] Selected Tasks: ['arc_easy', 'boolq', 'copa', 'mrpc', 'piqa', 'sst2', 'winogrande']
+2024-05-29:13:05:57,981 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-29:13:05:57,981 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/mnt/weka/peacock/experiments/llama/eval/checkpoint/llamav2-3b/hf/global_step40000', 'tokenizer': 'huggyllama/llama-13b'}
+2024-05-29:13:06:00,409 INFO     [huggingface.py:164] Using device 'cuda'
+/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/gpu_migration/torch/cuda/memory.py:36: UserWarning: No need to call empty_cache on HPU. It manages the memory internally in an effcient way.
+  warnings.warn(
+/usr/local/lib/python3.10/dist-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
+  warnings.warn(
+Downloading readme: 100%|██████████| 9.00k/9.00k [00:00<00:00, 16.1MB/s]
+Downloading data: 100%|██████████| 331k/331k [00:00<00:00, 3.98MB/s]
+Downloading data: 100%|██████████| 346k/346k [00:00<00:00, 4.47MB/s]
+Downloading data: 100%|██████████| 86.1k/86.1k [00:00<00:00, 1.07MB/s]
+Generating train split: 100%|██████████| 2251/2251 [00:00<00:00, 94036.70 examples/s]
+Generating test split: 100%|██████████| 2376/2376 [00:00<00:00, 318646.40 examples/s]
+Generating validation split: 100%|██████████| 570/570 [00:00<00:00, 189471.65 examples/s]
+2024-05-29:13:06:31,309 WARNING  [task.py:763] [Task: boolq] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-05-29:13:06:31,309 WARNING  [task.py:775] [Task: boolq] metric acc is defined, but higher_is_better is not. using default higher_is_better=True
+/usr/local/lib/python3.10/dist-packages/datasets/load.py:1486: FutureWarning: The repository for super_glue contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at https://hf.co/datasets/super_glue
+You can avoid this message in future by passing the argument `trust_remote_code=True`.
+Passing `trust_remote_code=True` will be mandatory to load this dataset from the next major release of `datasets`.
+  warnings.warn(
+Downloading builder script: 100%|██████████| 30.7k/30.7k [00:00<00:00, 41.2MB/s]
+Downloading readme: 100%|██████████| 18.2k/18.2k [00:00<00:00, 29.5MB/s]
+Downloading data: 100%|██████████| 4.12M/4.12M [00:00<00:00, 36.5MB/s]
+Generating train split: 100%|██████████| 9427/9427 [00:00<00:00, 21934.83 examples/s]
+Generating validation split: 100%|██████████| 3270/3270 [00:00<00:00, 21563.32 examples/s]
+Generating test split: 100%|██████████| 3245/3245 [00:00<00:00, 23042.93 examples/s]
+2024-05-29:13:06:35,208 WARNING  [task.py:763] [Task: copa] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-05-29:13:06:35,208 WARNING  [task.py:775] [Task: copa] metric acc is defined, but higher_is_better is not. using default higher_is_better=True
+Downloading data: 100%|██████████| 44.0k/44.0k [00:00<00:00, 60.3MB/s]
+Generating train split: 100%|██████████| 400/400 [00:00<00:00, 8149.86 examples/s]
+Generating validation split: 100%|██████████| 100/100 [00:00<00:00, 12525.17 examples/s]
+Generating test split: 100%|██████████| 500/500 [00:00<00:00, 15116.24 examples/s]
+2024-05-29:13:06:37,359 WARNING  [task.py:763] [Task: mrpc] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-05-29:13:06:37,359 WARNING  [task.py:775] [Task: mrpc] metric acc is defined, but higher_is_better is not. using default higher_is_better=True
+2024-05-29:13:06:37,360 WARNING  [task.py:763] [Task: mrpc] metric f1 is defined, but aggregation is not. using default aggregation=f1
+2024-05-29:13:06:37,360 WARNING  [task.py:775] [Task: mrpc] metric f1 is defined, but higher_is_better is not. using default higher_is_better=True
+Downloading readme: 100%|██████████| 35.3k/35.3k [00:00<00:00, 43.6MB/s]
+Downloading data: 100%|██████████| 649k/649k [00:00<00:00, 4.16MB/s]
+Downloading data: 100%|██████████| 75.7k/75.7k [00:00<00:00, 523kB/s]
+Downloading data: 100%|██████████| 308k/308k [00:00<00:00, 2.11MB/s]
+Generating train split: 100%|██████████| 3668/3668 [00:00<00:00, 416670.02 examples/s]
+Generating validation split: 100%|██████████| 408/408 [00:00<00:00, 175731.78 examples/s]
+Generating test split: 100%|██████████| 1725/1725 [00:00<00:00, 367155.91 examples/s]
+/usr/local/lib/python3.10/dist-packages/datasets/load.py:1486: FutureWarning: The repository for piqa contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at https://hf.co/datasets/piqa
+You can avoid this message in future by passing the argument `trust_remote_code=True`.
+Passing `trust_remote_code=True` will be mandatory to load this dataset from the next major release of `datasets`.
+  warnings.warn(
+Downloading builder script: 100%|██████████| 5.36k/5.36k [00:00<00:00, 11.9MB/s]
+Downloading readme: 100%|██████████| 8.41k/8.41k [00:00<00:00, 17.7MB/s]
+Downloading data: 100%|██████████| 1.82M/1.82M [00:00<00:00, 4.23MB/s]
+Downloading data: 100%|██████████| 815k/815k [00:00<00:00, 25.2MB/s]
+Generating train split: 100%|██████████| 16113/16113 [00:00<00:00, 23572.71 examples/s]
+Generating test split: 100%|██████████| 3084/3084 [00:00<00:00, 24639.24 examples/s]
+Generating validation split: 100%|██████████| 1838/1838 [00:00<00:00, 23687.17 examples/s]
+2024-05-29:13:06:48,144 WARNING  [task.py:763] [Task: sst2] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-05-29:13:06:48,145 WARNING  [task.py:775] [Task: sst2] metric acc is defined, but higher_is_better is not. using default higher_is_better=True
+Downloading data: 100%|██████████| 3.11M/3.11M [00:00<00:00, 20.4MB/s]
+Downloading data: 100%|██████████| 72.8k/72.8k [00:00<00:00, 498kB/s]
+Downloading data: 100%|██████████| 148k/148k [00:00<00:00, 1.03MB/s]
+Generating train split: 100%|██████████| 67349/67349 [00:00<00:00, 1421809.06 examples/s]
+Generating validation split: 100%|██████████| 872/872 [00:00<00:00, 372561.18 examples/s]
+Generating test split: 100%|██████████| 1821/1821 [00:00<00:00, 550910.82 examples/s]
+/usr/local/lib/python3.10/dist-packages/datasets/load.py:1486: FutureWarning: The repository for winogrande contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at https://hf.co/datasets/winogrande
+You can avoid this message in future by passing the argument `trust_remote_code=True`.
+Passing `trust_remote_code=True` will be mandatory to load this dataset from the next major release of `datasets`.
+  warnings.warn(
+Downloading builder script: 100%|██████████| 5.65k/5.65k [00:00<00:00, 11.3MB/s]
+Downloading readme: 100%|██████████| 9.97k/9.97k [00:00<00:00, 20.5MB/s]
+Downloading data: 100%|██████████| 3.40M/3.40M [00:00<00:00, 7.19MB/s]
+Generating train split: 100%|██████████| 40398/40398 [00:01<00:00, 24190.59 examples/s]
+Generating test split: 100%|██████████| 1767/1767 [00:00<00:00, 24297.63 examples/s]
+Generating validation split: 100%|██████████| 1267/1267 [00:00<00:00, 23882.36 examples/s]
+2024-05-29:13:07:01,178 INFO     [task.py:395] Building contexts for winogrande on rank 0...
+100%|██████████| 1267/1267 [00:00<00:00, 68124.44it/s]
+2024-05-29:13:07:01,263 INFO     [task.py:395] Building contexts for sst2 on rank 0...
+100%|██████████| 872/872 [00:00<00:00, 2555.88it/s]
+2024-05-29:13:07:01,634 INFO     [task.py:395] Building contexts for piqa on rank 0...
+100%|██████████| 1838/1838 [00:01<00:00, 1077.65it/s]
+2024-05-29:13:07:03,415 INFO     [task.py:395] Building contexts for mrpc on rank 0...
+100%|██████████| 408/408 [00:00<00:00, 1818.70it/s]
+2024-05-29:13:07:03,658 INFO     [task.py:395] Building contexts for copa on rank 0...
+100%|██████████| 100/100 [00:00<00:00, 70504.35it/s]
+2024-05-29:13:07:03,669 INFO     [task.py:395] Building contexts for boolq on rank 0...
+100%|██████████| 3270/3270 [00:01<00:00, 1984.82it/s]
+2024-05-29:13:07:05,448 INFO     [task.py:395] Building contexts for arc_easy on rank 0...
+100%|██████████| 2376/2376 [00:02<00:00, 1071.72it/s]
+2024-05-29:13:07:07,813 INFO     [evaluator.py:379] Running loglikelihood requests
+Running loglikelihood requests:   0%|          | 0/25011 [00:00<?, ?it/s]
+Passed argument batch_size = auto:1. Detecting largest batch size
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+Running loglikelihood requests: 100%|██████████| 25011/25011 [41:49<00:00,  9.97it/s]
+bootstrapping for stddev: f1_score
+
+
+100%|██████████| 100/100 [02:10<00:00,  1.30s/it]
+hf (pretrained=/mnt/weka/peacock/experiments/llama/eval/checkpoint/llamav2-3b/hf/global_step40000,tokenizer=huggyllama/llama-13b), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: auto (64)
+|  Tasks   |Version|Filter|n-shot| Metric |Value |   |Stderr|
+|----------|------:|------|-----:|--------|-----:|---|-----:|
+|winogrande|      1|none  |     0|acc     |0.5051|±  |0.0141|
+|sst2      |      1|none  |     0|acc     |0.4771|±  |0.0169|
+|piqa      |      1|none  |     0|acc     |0.5245|±  |0.0117|
+|          |       |none  |     0|acc_norm|0.4951|±  |0.0117|
+|mrpc      |      1|none  |     0|acc     |0.5123|±  |0.0248|
+|          |       |none  |     0|f1      |0.6106|±  |0.0255|
+|copa      |      1|none  |     0|acc     |0.6500|±  |0.0479|
+|boolq     |      2|none  |     0|acc     |0.5083|±  |0.0087|
+|arc_easy  |      1|none  |     0|acc     |0.2580|±  |0.0090|
+|          |       |none  |     0|acc_norm|0.2538|±  |0.0089|

lm-evaluation-harness/wandb/run-20240529_130547-x16dn3vu/files/requirements.txt

@@ -0,0 +1,154 @@
+DataProperty==1.0.1
+GitPython==3.1.43
+Jinja2==3.1.4
+Markdown==3.6
+MarkupSafe==2.1.5
+Pillow-SIMD==7.0.0.post3
+PyYAML==6.0
+Werkzeug==3.0.3
+absl-py==2.1.0
+accelerate==0.30.1
+aiohttp==3.9.5
+aiosignal==1.3.1
+async-timeout==4.0.3
+attrs==23.2.0
+av==9.2.0
+cachetools==5.3.3
+certifi==2024.2.2
+cffi==1.15.1
+cfgv==3.4.0
+chardet==5.2.0
+charset-normalizer==3.3.2
+click==8.1.7
+cmake==3.29.2
+colorama==0.4.6
+datasets==2.19.1
+deepspeed==0.12.4+hpu.synapse.v1.15.1
+dill==0.3.8
+distlib==0.3.8
+docker-pycreds==0.4.0
+einops==0.8.0
+evaluate==0.4.2
+exceptiongroup==1.2.1
+expecttest==0.2.1
+filelock==3.14.0
+frozenlist==1.4.1
+fsspec==2024.3.1
+gitdb==4.0.11
+google-auth-oauthlib==0.4.6
+google-auth==2.29.0
+grpcio==1.63.0
+habana-media-loader==1.15.1.15
+habana-pyhlml==1.15.1.15
+habana-torch-dataloader==1.15.1.15
+habana-torch-plugin==1.15.1.15
+habana_gpu_migration==1.15.1.15
+habana_quantization_toolkit==1.15.1.15
+hjson==3.1.0
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+lightning==2.2.0.post0
+lm_eval==0.4.2
+lm_eval==0.4.2
+lm_eval==0.4.2
+lxml==5.2.2
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+more-itertools==10.2.0
+mpi4py==3.1.4
+mpmath==1.3.0
+multidict==6.0.5
+multiprocess==0.70.16
+networkx==3.3
+ninja==1.11.1.1
+nltk==3.8.1
+nodeenv==1.8.0
+numexpr==2.10.0
+numpy==1.23.5
+oauthlib==3.2.2
+packaging==24.0
+pandas==2.0.1
+pathspec==0.12.1
+pathvalidate==3.2.0
+peft==0.11.1
+perfetto==0.7.0
+pip==22.0.2
+pip==23.3.1
+platformdirs==4.2.1
+pluggy==1.5.0
+portalocker==2.8.2
+pre-commit==3.3.3
+pretty-errors==1.2.25
+protobuf==3.20.3
+psutil==5.9.8
+py-cpuinfo==9.0.0
+pyarrow-hotfix==0.6
+pyarrow==16.1.0
+pyasn1==0.6.0
+pyasn1_modules==0.4.0
+pybind11==2.10.4
+pycparser==2.22
+pydantic==1.10.13
+pynvml==8.0.4
+pytablewriter==1.2.0
+pytest==8.2.0
+python-dateutil==2.9.0.post0
+pytorch-lightning==2.2.4
+pytz==2024.1
+regex==2023.5.5
+requests-oauthlib==2.0.0
+requests==2.31.0
+rouge_score==0.1.2
+rsa==4.9
+sacrebleu==2.4.2
+safetensors==0.4.3
+scikit-learn==1.5.0
+scipy==1.13.1
+sentencepiece==0.2.0
+sentry-sdk==2.3.1
+setproctitle==1.3.3
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+six==1.16.0
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+symengine==0.11.0
+sympy==1.12
+tabledata==1.3.3
+tabulate==0.9.0
+tcolorpy==0.1.6
+tdqm==0.0.1
+tensorboard-data-server==0.6.1
+tensorboard-plugin-wit==1.8.1
+tensorboard==2.11.2
+threadpoolctl==3.5.0
+tokenizers==0.15.2
+tomli==2.0.1
+torch==2.2.0a0+git8964477
+torch_tb_profiler==0.4.0
+torchaudio==2.2.0+08901ad
+torchdata==0.7.1+5e6f7b7
+torchmetrics==1.4.0
+torchtext==0.17.0+400da5c
+torchvision==0.17.0+b2383d4
+tqdm-multiprocess==0.0.11
+tqdm==4.66.4
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+tzdata==2024.1
+urllib3==1.26.18
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+wandb==0.17.0
+wheel==0.37.1
+wheel==0.43.0
+word2number==1.1
+xxhash==3.4.1
+yamllint==1.35.1
+yarl==1.9.4
+zstandard==0.22.0

lm-evaluation-harness/wandb/run-20240529_130547-x16dn3vu/files/wandb-metadata.json

@@ -0,0 +1,850 @@
+{
+    "os": "Linux-5.15.0-92-generic-x86_64-with-glibc2.35",
+    "python": "3.10.12",
+    "heartbeatAt": "2024-05-29T13:05:48.238638",
+    "startedAt": "2024-05-29T13:05:47.742131",
+    "docker": null,
+    "cuda": null,
+    "args": [
+        "--model",
+        "hf",
+        "--model_args",
+        "pretrained=/mnt/weka/peacock/experiments/llama/eval/checkpoint/llamav2-3b/hf/global_step40000,tokenizer=huggyllama/llama-13b",
+        "--tasks",
+        "winogrande,sst2,mrpc,arc_easy,copa,piqa,boolq",
+        "--batch_size",
+        "auto",
+        "--wandb_args",
+        "project=english-eval,group=exp1"
+    ],
+    "state": "running",
+    "program": "-m lm_eval.__main__",
+    "codePathLocal": null,
+    "git": {
+        "remote": "https://github.com/EleutherAI/lm-evaluation-harness",
+        "commit": null
+    },
+    "email": null,
+    "root": "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness",
+    "host": "peacock-evaluation-debug-20-worker-0",
+    "username": "root",
+    "executable": "/usr/bin/python3",
+    "cpu_count": 80,
+    "cpu_count_logical": 160,
+    "cpu_freq": {
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+        "max": 3400.0
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+        {
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+            "min": 800.0,
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+        {
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+            "max": 3400.0
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+        {
+            "current": 2300.0,
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+        {
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+      dataset_name: ARC-Easy
+      training_split: train
+      validation_split: validation
+      test_split: test
+      doc_to_text: 'Question: {{question}}
+
+        Answer:'
+      doc_to_target: '{{choices.label.index(answerKey)}}'
+      doc_to_choice: '{{choices.text}}'
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
+      num_fewshot: 0
+      metric_list:
+      - metric: acc
+        aggregation: mean
+        higher_is_better: true
+      - metric: acc_norm
+        aggregation: mean
+        higher_is_better: true
+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: true
+      doc_to_decontamination_query: 'Question: {{question}}
+
+        Answer:'
+      metadata:
+        version: 1.0
+    boolq:
+      task: boolq
+      group:
+      - super-glue-lm-eval-v1
+      dataset_path: super_glue
+      dataset_name: boolq
+      training_split: train
+      validation_split: validation
+      doc_to_text: '{{passage}}
+
+        Question: {{question}}?
+
+        Answer:'
+      doc_to_target: label
+      doc_to_choice:
+      - 'no'
+      - 'yes'
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
+      num_fewshot: 0
+      metric_list:
+      - metric: acc
+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: true
+      doc_to_decontamination_query: passage
+      metadata:
+        version: 2.0
+    copa:
+      task: copa
+      group:
+      - super-glue-lm-eval-v1
+      dataset_path: super_glue
+      dataset_name: copa
+      training_split: train
+      validation_split: validation
+      doc_to_text: "def doc_to_text(doc):\n    # Drop the period\n    connector =\
+        \ {\n        \"cause\": \"because\",\n        \"effect\": \"therefore\",\n\
+        \    }[doc[\"question\"]]\n    return doc[\"premise\"].strip()[:-1] + f\"\
+        \ {connector}\"\n"
+      doc_to_target: "def doc_to_target(doc):\n    correct_choice = doc[\"choice1\"\
+        ] if doc[\"label\"] == 0 else doc[\"choice2\"]\n    # Connect the sentences\n\
+        \    return \" \" + convert_choice(correct_choice)\n"
+      doc_to_choice: "def doc_to_choice(doc):\n    return [\" \" + convert_choice(doc[\"\
+        choice1\"]), \" \" + convert_choice(doc[\"choice2\"])]\n"
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
+      num_fewshot: 0
+      metric_list:
+      - metric: acc
+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: false
+      metadata:
+        version: 1.0
+    indic_arc_challenge_hi:
+      task: indic_arc_challenge_hi
+      group: Cognitive-Lab/Indic-ARC-Challenge
+      dataset_path: Cognitive-Lab/Indic-ARC-Challenge
+      dataset_name: hi
+      test_split: test
+      doc_to_text: 'Question: {{translated_question}}
+
+        Answer:'
+      doc_to_target: '{{translated_choices.label.index(answerKey)}}'
+      doc_to_choice: '{{translated_choices.text}}'
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
+      num_fewshot: 0
+      metric_list:
+      - metric: acc
+        aggregation: mean
+        higher_is_better: true
+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: true
+      doc_to_decontamination_query: 'Question: {{translated_question}}
+
+        Answer:'
+      metadata:
+        version: 1.0
+    indic_arc_easy_hi:
+      task: indic_arc_easy_hi
+      group: Cognitive-Lab/Indic-ARC-Easy
+      dataset_path: Cognitive-Lab/Indic-ARC-Easy
+      dataset_name: hi
+      test_split: test
+      doc_to_text: 'Question: {{translated_question}}
+
+        Answer:'
+      doc_to_target: '{{translated_choices.label.index(answerKey)}}'
+      doc_to_choice: '{{translated_choices.text}}'
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
+      num_fewshot: 0
+      metric_list:
+      - metric: acc
+        aggregation: mean
+        higher_is_better: true
+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: true
+      doc_to_decontamination_query: 'Question: {{translated_question}}
+
+        Answer:'
+      metadata:
+        version: 1.0
+    indic_boolq_hi:
+      task: indic_boolq_hi
+      group: Cognitive-Lab/Indic-BoolQ
+      dataset_path: Cognitive-Lab/Indic-BoolQ
+      dataset_name: hi
+      validation_split: validation
+      doc_to_text: 'Passage: {translated_passage}
+
+        Question: {translated_question.strip()}
+
+        Answer:'
+      doc_to_target: answer
+      doc_to_choice:
+      - 'true'
+      - 'false'
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
+      num_fewshot: 0
+      metric_list:
+      - metric: acc
+        aggregation: mean
+        higher_is_better: true
+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: false
+      metadata:
+        version: 1.0
+    mrpc:
+      task: mrpc
+      group: glue
+      dataset_path: glue
+      dataset_name: mrpc
+      training_split: train
+      validation_split: validation
+      doc_to_text: 'Sentence 1: {{sentence1}}
+
+        Sentence 2: {{sentence2}}
+
+        Question: Do both sentences mean the same thing?
+
+        Answer:'
+      doc_to_target: label
+      doc_to_choice:
+      - 'no'
+      - 'yes'
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
+      num_fewshot: 0
+      metric_list:
+      - metric: acc
+      - metric: f1
+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: false
+      metadata:
+        version: 1.0
+    piqa:
+      task: piqa
+      dataset_path: piqa
+      training_split: train
+      validation_split: validation
+      doc_to_text: 'Question: {{goal}}
+
+        Answer:'
+      doc_to_target: label
+      doc_to_choice: '{{[sol1, sol2]}}'
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
+      num_fewshot: 0
+      metric_list:
+      - metric: acc
+        aggregation: mean
+        higher_is_better: true
+      - metric: acc_norm
+        aggregation: mean
+        higher_is_better: true
+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: true
+      doc_to_decontamination_query: goal
+      metadata:
+        version: 1.0
+    sst2:
+      task: sst2
+      group: glue
+      dataset_path: glue
+      dataset_name: sst2
+      training_split: train
+      validation_split: validation
+      doc_to_text: '{{sentence}}
+
+        Question: Is this sentence positive or negative?
+
+        Answer:'
+      doc_to_target: label
+      doc_to_choice:
+      - negative
+      - positive
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
+      num_fewshot: 0
+      metric_list:
+      - metric: acc
+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: false
+      metadata:
+        version: 1.0
+    winogrande:
+      task: winogrande
+      dataset_path: winogrande
+      dataset_name: winogrande_xl
+      training_split: train
+      validation_split: validation
+      doc_to_text: "def doc_to_text(doc):\n    answer_to_num = {\"1\": 0, \"2\": 1}\n\
+        \    return answer_to_num[doc[\"answer\"]]\n"
+      doc_to_target: "def doc_to_target(doc):\n    idx = doc[\"sentence\"].index(\"\
+        _\") + 1\n    return doc[\"sentence\"][idx:].strip()\n"
+      doc_to_choice: "def doc_to_choice(doc):\n    idx = doc[\"sentence\"].index(\"\
+        _\")\n    options = [doc[\"option1\"], doc[\"option2\"]]\n    return [doc[\"\
+        sentence\"][:idx] + opt for opt in options]\n"
+      description: ''
+      target_delimiter: ' '
+      fewshot_delimiter: '
+
+
+        '
+      num_fewshot: 0
+      metric_list:
+      - metric: acc
+        aggregation: mean
+        higher_is_better: true
+      output_type: multiple_choice
+      repeats: 1
+      should_decontaminate: true
+      doc_to_decontamination_query: sentence
+      metadata:
+        version: 1.0
+cli_configs:
+  desc: null
+  value:
+    model: hf
+    model_args: pretrained=/mnt/weka/peacock/experiments/llama/eval/checkpoint-enhibn-updated/llamav2-3b/hf/global_step226000,tokenizer=/mnt/weka/peacock/tokenization/trained-tokenizer/enhiben_50k_hf/ConvertedTokenizer
+    batch_size: auto
+    batch_sizes:
+    - 64
+    device: null
+    use_cache: null
+    limit: null
+    bootstrap_iters: 100000
+    gen_kwargs: null

lm-evaluation-harness/wandb/run-20240608_174352-w0xyfhqg/files/requirements.txt

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lm-evaluation-harness/wandb/run-20240608_174352-w0xyfhqg/files/wandb-metadata.json

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+    "os": "Linux-5.15.0-92-generic-x86_64-with-glibc2.35",
+    "python": "3.10.12",
+    "heartbeatAt": "2024-06-08T17:43:53.449598",
+    "startedAt": "2024-06-08T17:43:52.999993",
+    "docker": null,
+    "cuda": null,
+    "args": [
+        "--model",
+        "hf",
+        "--model_args",
+        "pretrained=/mnt/weka/peacock/experiments/llama/eval/checkpoint-enhibn-updated/llamav2-3b/hf/global_step226000,tokenizer=/mnt/weka/peacock/tokenization/trained-tokenizer/enhiben_50k_hf/ConvertedTokenizer",
+        "--tasks",
+        "winogrande,sst2,mrpc,arc_easy,copa,piqa,boolq,indic_arc_easy_hi,indic_arc_challenge_hi,indic_boolq_hi",
+        "--batch_size",
+        "auto",
+        "--wandb_args",
+        "project=engl-hi-eval,name=globalstep_226000,group=exp2"
+    ],
+    "state": "running",
+    "program": "-m lm_eval.__main__",
+    "codePathLocal": null,
+    "git": {
+        "remote": "https://github.com/EleutherAI/lm-evaluation-harness",
+        "commit": null
+    },
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'num_fewshot': 0, 'metric_list': [{'metric': 'acc'}, {'metric': 'f1'}], 'output_type': 'multiple_choice', 'repeats': 1, 'should_decontaminate': False, 'metadata': {'version': 1.0}}, 'piqa': {'task': 'piqa', 'dataset_path': 'piqa', 'training_split': 'train', 'validation_split': 'validation', 'doc_to_text': 'Question: {{goal}}\nAnswer:', 'doc_to_target': 'label', 'doc_to_choice': '{{[sol1, sol2]}}', 'description': '', 'target_delimiter': ' ', 'fewshot_delimiter': '\n\n', 'num_fewshot': 0, 'metric_list': [{'metric': 'acc', 'aggregation': 'mean', 'higher_is_better': True}, {'metric': 'acc_norm', 'aggregation': 'mean', 'higher_is_better': True}], 'output_type': 'multiple_choice', 'repeats': 1, 'should_decontaminate': True, 'doc_to_decontamination_query': 'goal', 'metadata': {'version': 1.0}}, 'sst2': {'task': 'sst2', 'group': 'glue', 'dataset_path': 'glue', 'dataset_name': 'sst2', 'training_split': 'train', 'validation_split': 'validation', 'doc_to_text': '{{sentence}}\nQuestion: Is this sentence positive or negative?\nAnswer:', 'doc_to_target': 'label', 'doc_to_choice': ['negative', 'positive'], 'description': '', 'target_delimiter': ' ', 'fewshot_delimiter': '\n\n', 'num_fewshot': 0, 'metric_list': [{'metric': 'acc'}], 'output_type': 'multiple_choice', 'repeats': 1, 'should_decontaminate': False, 'metadata': {'version': 1.0}}, 'winogrande': {'task': 'winogrande', 'dataset_path': 'winogrande', 'dataset_name': 'winogrande_xl', 'training_split': 'train', 'validation_split': 'validation', 'doc_to_text': 'def doc_to_text(doc):\n    answer_to_num = {"1": 0, "2": 1}\n    return answer_to_num[doc["answer"]]\n', 'doc_to_target': 'def doc_to_target(doc):\n    idx = doc["sentence"].index("_") + 1\n    return doc["sentence"][idx:].strip()\n', 'doc_to_choice': 'def doc_to_choice(doc):\n    idx = doc["sentence"].index("_")\n    options = [doc["option1"], doc["option2"]]\n    return [doc["sentence"][:idx] + opt for opt in options]\n', 'description': '', 'target_delimiter': ' ', 'fewshot_delimiter': '\n\n', 'num_fewshot': 0, 'metric_list': [{'metric': 'acc', 'aggregation': 'mean', 'higher_is_better': True}], 'output_type': 'multiple_choice', 'repeats': 1, 'should_decontaminate': True, 'doc_to_decontamination_query': 'sentence', 'metadata': {'version': 1.0}}}, 'cli_configs': {'model': 'hf', 'model_args': 'pretrained=/mnt/weka/peacock/experiments/llama/eval/checkpoint-enhibn-updated/llamav2-3b/hf/global_step226000,tokenizer=/mnt/weka/peacock/tokenization/trained-tokenizer/enhiben_50k_hf/ConvertedTokenizer', 'batch_size': 'auto', 'batch_sizes': [64], 'device': None, 'use_cache': None, 'limit': None, 'bootstrap_iters': 100000, 'gen_kwargs': None}}
+2024-06-08 18:56:35,834 INFO    MainThread:25353 [wandb_run.py:_finish():2109] finishing run smlgenai/engl-hi-eval/w0xyfhqg
+2024-06-08 18:56:35,835 INFO    MainThread:25353 [wandb_run.py:_atexit_cleanup():2349] got exitcode: 0
+2024-06-08 18:56:35,859 INFO    MainThread:25353 [wandb_run.py:_restore():2332] restore
+2024-06-08 18:56:35,859 INFO    MainThread:25353 [wandb_run.py:_restore():2338] restore done
+2024-06-08 18:56:42,473 INFO    MainThread:25353 [wandb_run.py:_footer_history_summary_info():4008] rendering history
+2024-06-08 18:56:42,474 INFO    MainThread:25353 [wandb_run.py:_footer_history_summary_info():4040] rendering summary
+2024-06-08 18:56:42,480 INFO    MainThread:25353 [wandb_run.py:_footer_sync_info():3967] logging synced files

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