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ckpts/universal/global_step20/zero/18.mlp.dense_h_to_4h.weight/fp32.pt

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

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lm-evaluation-harness/wandb/run-20240522_185758-pjdiqmhu/files/config.yaml

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+_wandb:
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+  value:
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+    cli_version: 0.17.0
+    framework: huggingface
+    huggingface_version: 4.41.0
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lm-evaluation-harness/wandb/run-20240522_185758-pjdiqmhu/files/output.log

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+
+2024-05-22:18:57:59,244 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-22:18:58:07,648 INFO     [__main__.py:335] Selected Tasks: ['arc_easy', 'hellaswag', 'mrpc', 'openbookqa', 'sst2', 'winogrande']
+2024-05-22:18:58:07,649 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-22:18:58:07,649 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/mnt/weka/peacock/experiments/llama/checkpoint/llamav2-3b//hf_ckpt//global_step26000'}
+2024-05-22:18:58:09,997 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_step26000 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_step26000/tree/main' for available files.

lm-evaluation-harness/wandb/run-20240522_185758-pjdiqmhu/files/requirements.txt

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+pandas==2.0.1
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+pathvalidate==3.2.0
+peft==0.11.1
+perfetto==0.7.0
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+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
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+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
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+torch_tb_profiler==0.4.0
+torchaudio==2.2.0+08901ad
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+torchvision==0.17.0+b2383d4
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+typepy==1.3.2
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+tzdata==2024.1
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lm-evaluation-harness/wandb/run-20240523_042058-x7tfzrt9/files/output.log

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+
+2024-05-23:04:20:59,243 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-23:04:21:08,631 INFO     [__main__.py:335] Selected Tasks: ['arc_easy', 'hellaswag', 'mrpc', 'openbookqa', 'sst2', 'winogrande']
+2024-05-23:04:21:08,633 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-23:04:21:08,633 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/mnt/weka/peacock/experiments/llama/checkpoint/llamav2-3b//hf_ckpt//global_step100'}
+2024-05-23:04:21:10,954 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_step100 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_step100/tree/main' for available files.

lm-evaluation-harness/wandb/run-20240523_042058-x7tfzrt9/files/requirements.txt

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+lm_eval==0.4.2
+lm_eval==0.4.2
+lm_eval==0.4.2
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+mbstrdecoder==1.1.3
+megatron-lm==1.1.5
+more-itertools==10.2.0
+mpi4py==3.1.4
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+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
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+pyasn1_modules==0.4.0
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+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
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+torch==2.2.0a0+git8964477
+torch_tb_profiler==0.4.0
+torchaudio==2.2.0+08901ad
+torchdata==0.7.1+5e6f7b7
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+torchtext==0.17.0+400da5c
+torchvision==0.17.0+b2383d4
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+typepy==1.3.2
+typing_extensions==4.11.0
+tzdata==2024.1
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+xxhash==3.4.1
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+    huggingface_version: 4.41.1
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+    is_kaggle_kernel: false
+    start_time: 1716467468
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lm-evaluation-harness/wandb/run-20240523_123108-q1qey2rv/files/output.log

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+
+2024-05-23:12:31:09,051 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-23:12:31:17,526 INFO     [__main__.py:335] Selected Tasks: ['arc_easy', 'hellaswag', 'mrpc', 'openbookqa', 'sst2', 'winogrande']
+2024-05-23:12:31:17,527 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-23:12:31:17,527 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/mnt/weka/peacock/experiments/llama/checkpoint/llamav2-3b//hf_ckpt//global_step14000'}
+2024-05-23:12:31:19,821 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_step14000 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_step14000/tree/main' for available files.

lm-evaluation-harness/wandb/run-20240523_123108-q1qey2rv/files/requirements.txt

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+GitPython==3.1.43
+Jinja2==3.1.4
+Markdown==3.6
+MarkupSafe==2.1.5
+Pillow-SIMD==7.0.0.post3
+PyYAML==6.0
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+certifi==2024.2.2
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+chardet==5.2.0
+charset-normalizer==3.3.2
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+colorama==0.4.6
+datasets==2.19.1
+deepspeed==0.12.4+hpu.synapse.v1.15.1
+dill==0.3.8
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+docker-pycreds==0.4.0
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+evaluate==0.4.2
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+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
+lightning-habana==1.4.0
+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
+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
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+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==2.3.0
+setproctitle==1.3.3
+setuptools==59.6.0
+setuptools==69.5.1
+six==1.16.0
+smmap==5.0.1
+sqlitedict==2.1.0
+symengine==0.11.0
+sympy==1.12
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+tcolorpy==0.1.6
+tdqm==0.0.1
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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
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lm-evaluation-harness/wandb/run-20240530_064611-ljd1x9e1/files/config.yaml

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+    cli_version: 0.17.0
+    framework: huggingface
+    huggingface_version: 4.36.2
+    is_jupyter_run: false
+    is_kaggle_kernel: false
+    start_time: 1717051571
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lm-evaluation-harness/wandb/run-20240530_064611-ljd1x9e1/files/output.log

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+
+2024-05-30:06:46:12,558 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-30:06:46:21,837 INFO     [__main__.py:335] Selected Tasks: ['arc_easy', 'boolq', 'copa', 'mrpc', 'piqa', 'sst2', 'winogrande']
+2024-05-30:06:46:21,838 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-30:06:46:21,838 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/mnt/weka/peacock/experiments/llama/eval/checkpoint-english/llamav2-3b/hf/global_step40000', 'tokenizer': '/mnt/weka/peacock/tokenization/trained-tokenizer/enhiben_50k/'}
+2024-05-30:06:46:24,120 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(
+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 237, in __init__
+    self._create_tokenizer(
+  File "/mnt/weka/peacock/idc/cronscript/lm-evaluation-harness/lm_eval/models/huggingface.py", line 630, in _create_tokenizer
+    self.tokenizer = transformers.AutoTokenizer.from_pretrained(
+  File "/usr/local/lib/python3.10/dist-packages/transformers/models/auto/tokenization_auto.py", line 752, in from_pretrained
+    config = AutoConfig.from_pretrained(
+  File "/usr/local/lib/python3.10/dist-packages/transformers/models/auto/configuration_auto.py", line 1082, 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 644, 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 699, in _get_config_dict
+    resolved_config_file = cached_file(
+  File "/usr/local/lib/python3.10/dist-packages/transformers/utils/hub.py", line 360, in cached_file
+    raise EnvironmentError(
+OSError: /mnt/weka/peacock/tokenization/trained-tokenizer/enhiben_50k/ does not appear to have a file named config.json. Checkout 'https://huggingface.co//mnt/weka/peacock/tokenization/trained-tokenizer/enhiben_50k//main' for available files.

lm-evaluation-harness/wandb/run-20240530_064611-ljd1x9e1/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
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+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
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+      5: 0.17.1
+      6: 4.36.2
+      8:
+      - 5
+      13: linux-x86_64
+task_configs:
+  desc: null
+  value:
+    arc_easy:
+      task: arc_easy
+      group:
+      - ai2_arc
+      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:
+        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_step200000,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_162527-0vroecl5/files/output.log

@@ -0,0 +1,741 @@
+
+2024-06-08:16:25:27,912 INFO     [__main__.py:251] Verbosity set to INFO
+2024-06-08:16:25:37,214 INFO     [__main__.py:335] Selected Tasks: ['arc_easy', 'boolq', 'copa', 'indic_arc_challenge_hi', 'indic_arc_easy_hi', 'indic_boolq_hi', 'mrpc', 'piqa', 'sst2', 'winogrande']
+2024-06-08:16:25:37,215 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-06-08:16:25:37,215 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/mnt/weka/peacock/experiments/llama/eval/checkpoint-enhibn-updated/llamav2-3b/hf/global_step200000', 'tokenizer': '/mnt/weka/peacock/tokenization/trained-tokenizer/enhiben_50k_hf/ConvertedTokenizer'}
+2024-06-08:16:25:39,548 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(
+Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
+2024-06-08:16:26:07,201 WARNING  [task.py:763] [Task: boolq] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-06-08:16:26:07,202 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:1491: 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(
+2024-06-08:16:26:08,968 WARNING  [task.py:763] [Task: copa] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-06-08:16:26:08,969 WARNING  [task.py:775] [Task: copa] metric acc is defined, but higher_is_better is not. using default higher_is_better=True
+2024-06-08:16:26:11,891 WARNING  [task.py:322] [Task: indic_arc_challenge_hi] has_training_docs and has_validation_docs are False, using test_docs as fewshot_docs but this is not recommended.
+2024-06-08:16:26:11,892 WARNING  [task.py:322] [Task: indic_arc_challenge_hi] has_training_docs and has_validation_docs are False, using test_docs as fewshot_docs but this is not recommended.
+2024-06-08:16:26:13,583 WARNING  [task.py:322] [Task: indic_arc_easy_hi] has_training_docs and has_validation_docs are False, using test_docs as fewshot_docs but this is not recommended.
+2024-06-08:16:26:13,584 WARNING  [task.py:322] [Task: indic_arc_easy_hi] has_training_docs and has_validation_docs are False, using test_docs as fewshot_docs but this is not recommended.
+2024-06-08:16:26:15,294 WARNING  [task.py:763] [Task: mrpc] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-06-08:16:26:15,295 WARNING  [task.py:775] [Task: mrpc] metric acc is defined, but higher_is_better is not. using default higher_is_better=True
+2024-06-08:16:26:15,295 WARNING  [task.py:763] [Task: mrpc] metric f1 is defined, but aggregation is not. using default aggregation=f1
+2024-06-08:16:26:15,295 WARNING  [task.py:775] [Task: mrpc] metric f1 is defined, but higher_is_better is not. using default higher_is_better=True
+/usr/local/lib/python3.10/dist-packages/datasets/load.py:1491: 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(
+2024-06-08:16:26:20,869 WARNING  [task.py:763] [Task: sst2] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-06-08:16:26:20,870 WARNING  [task.py:775] [Task: sst2] 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:1491: 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(
+2024-06-08:16:26:28,220 INFO     [task.py:395] Building contexts for winogrande on rank 0...
+100%|██████████| 1267/1267 [00:00<00:00, 69412.01it/s]
+2024-06-08:16:26:28,302 INFO     [task.py:395] Building contexts for sst2 on rank 0...
+100%|██████████| 872/872 [00:00<00:00, 2543.15it/s]
+2024-06-08:16:26:28,673 INFO     [task.py:395] Building contexts for piqa on rank 0...
+100%|██████████| 1838/1838 [00:01<00:00, 1092.20it/s]
+2024-06-08:16:26:30,430 INFO     [task.py:395] Building contexts for mrpc on rank 0...
+100%|██████████| 408/408 [00:00<00:00, 1841.43it/s]
+2024-06-08:16:26:30,669 INFO     [task.py:395] Building contexts for indic_boolq_hi on rank 0...
+100%|██████████| 3270/3270 [00:01<00:00, 3117.32it/s]
+2024-06-08:16:26:31,886 INFO     [task.py:395] Building contexts for indic_arc_easy_hi on rank 0...
+100%|██████████| 2376/2376 [00:02<00:00, 1124.51it/s]
+2024-06-08:16:26:34,234 INFO     [task.py:395] Building contexts for indic_arc_challenge_hi on rank 0...
+100%|██████████| 1172/1172 [00:01<00:00, 1118.52it/s]
+2024-06-08:16:26:35,405 INFO     [task.py:395] Building contexts for copa on rank 0...
+100%|██████████| 100/100 [00:00<00:00, 7372.92it/s]
+2024-06-08:16:26:35,426 INFO     [task.py:395] Building contexts for boolq on rank 0...
+100%|██████████| 3270/3270 [00:01<00:00, 1977.64it/s]
+2024-06-08:16:26:37,214 INFO     [task.py:395] Building contexts for arc_easy on rank 0...
+100%|██████████| 2376/2376 [00:02<00:00, 1054.15it/s]
+2024-06-08:16:26:39,611 INFO     [evaluator.py:379] Running loglikelihood requests
+Token indices sequence length is longer than the specified maximum sequence length for this model (1333 > 1024). Running this sequence through the model will result in indexing errors
+Running loglikelihood requests:   0%|          | 0/45739 [00:00<?, ?it/s]
+Passed argument batch_size = auto:1. Detecting largest batch size
+
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+Running loglikelihood requests: 100%|██████████| 45739/45739 [1:07:49<00:00, 11.24it/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-enhibn-updated/llamav2-3b/hf/global_step200000,tokenizer=/mnt/weka/peacock/tokenization/trained-tokenizer/enhiben_50k_hf/ConvertedTokenizer), 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     |0.4949|±  |0.0141|
+|sst2                  |      1|none  |     0|acc     |0.5126|±  |0.0169|
+|piqa                  |      1|none  |     0|acc     |0.5212|±  |0.0117|
+|                      |       |none  |     0|acc_norm|0.4897|±  |0.0117|
+|mrpc                  |      1|none  |     0|acc     |0.3162|±  |0.0230|
+|                      |       |none  |     0|f1      |0.0000|±  |0.0000|
+|indic_boolq_hi        |      1|none  |     0|acc     |0.6217|±  |0.0085|
+|indic_arc_easy_hi     |      1|none  |     0|acc     |0.2458|±  |0.0088|
+|indic_arc_challenge_hi|      1|none  |     0|acc     |0.2133|±  |0.0120|
+|copa                  |      1|none  |     0|acc     |0.5600|±  |0.0499|
+|boolq                 |      2|none  |     0|acc     |0.3783|±  |0.0085|
+|arc_easy              |      1|none  |     0|acc     |0.2609|±  |0.0090|
+|                      |       |none  |     0|acc_norm|0.2630|±  |0.0090|

lm-evaluation-harness/wandb/run-20240608_162527-0vroecl5/files/requirements.txt

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lm-evaluation-harness/wandb/run-20240608_162527-0vroecl5/files/wandb-summary.json

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lm-evaluation-harness/wandb/run-20240608_174352-w0xyfhqg/files/media/table/evaluation/eval_results_1_9d3400db6e1cfeedfe03.table.json

@@ -0,0 +1 @@
+{"columns": ["Tasks", "Version", "Filter", "num_fewshot", "Metric", "Value", "Stderr"], "data": [["winogrande", 1.0, "none", 0, "acc", "0.4972375690607735", "0.0141"], ["sst2", 1.0, "none", 0, "acc", "0.5068807339449541", "0.0169"], ["piqa", 1.0, "none", 0, "acc", "0.5206746463547334", "0.0117"], ["piqa", 1.0, "none", 0, "acc_norm", "0.500544069640914", "0.0117"], ["mrpc", 1.0, "none", 0, "acc", "0.3161764705882353", "0.0230"], ["mrpc", 1.0, "none", 0, "f1", "0.0", "0.0000"], ["indic_boolq_hi", 1.0, "none", 0, "acc", "0.6217125382262997", "0.0085"], ["indic_arc_easy_hi", 1.0, "none", 0, "acc", "0.24326599326599327", "0.0088"], ["indic_arc_challenge_hi", 1.0, "none", 0, "acc", "0.21160409556313994", "0.0119"], ["copa", 1.0, "none", 0, "acc", "0.59", "0.0494"], ["boolq", 2.0, "none", 0, "acc", "0.3782874617737003", "0.0085"], ["arc_easy", 1.0, "none", 0, "acc", "0.2588383838383838", "0.0090"], ["arc_easy", 1.0, "none", 0, "acc_norm", "0.2558922558922559", "0.0090"]]}

lm-evaluation-harness/wandb/run-20240608_174352-w0xyfhqg/files/output.log

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+
+2024-06-08:17:43:53,660 INFO     [__main__.py:251] Verbosity set to INFO
+2024-06-08:17:44:02,776 INFO     [__main__.py:335] Selected Tasks: ['arc_easy', 'boolq', 'copa', 'indic_arc_challenge_hi', 'indic_arc_easy_hi', 'indic_boolq_hi', 'mrpc', 'piqa', 'sst2', 'winogrande']
+2024-06-08:17:44:02,776 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-06-08:17:44:02,777 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'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'}
+2024-06-08:17:44:05,104 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(
+Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
+2024-06-08:17:44:34,370 WARNING  [task.py:763] [Task: boolq] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-06-08:17:44:34,371 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:1491: 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(
+2024-06-08:17:44:36,566 WARNING  [task.py:763] [Task: copa] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-06-08:17:44:36,566 WARNING  [task.py:775] [Task: copa] metric acc is defined, but higher_is_better is not. using default higher_is_better=True
+2024-06-08:17:44:39,619 WARNING  [task.py:322] [Task: indic_arc_challenge_hi] has_training_docs and has_validation_docs are False, using test_docs as fewshot_docs but this is not recommended.
+2024-06-08:17:44:39,620 WARNING  [task.py:322] [Task: indic_arc_challenge_hi] has_training_docs and has_validation_docs are False, using test_docs as fewshot_docs but this is not recommended.
+2024-06-08:17:44:41,111 WARNING  [task.py:322] [Task: indic_arc_easy_hi] has_training_docs and has_validation_docs are False, using test_docs as fewshot_docs but this is not recommended.
+2024-06-08:17:44:41,112 WARNING  [task.py:322] [Task: indic_arc_easy_hi] has_training_docs and has_validation_docs are False, using test_docs as fewshot_docs but this is not recommended.
+2024-06-08:17:44:42,813 WARNING  [task.py:763] [Task: mrpc] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-06-08:17:44:42,813 WARNING  [task.py:775] [Task: mrpc] metric acc is defined, but higher_is_better is not. using default higher_is_better=True
+2024-06-08:17:44:42,813 WARNING  [task.py:763] [Task: mrpc] metric f1 is defined, but aggregation is not. using default aggregation=f1
+2024-06-08:17:44:42,813 WARNING  [task.py:775] [Task: mrpc] metric f1 is defined, but higher_is_better is not. using default higher_is_better=True
+/usr/local/lib/python3.10/dist-packages/datasets/load.py:1491: 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(
+2024-06-08:17:44:48,408 WARNING  [task.py:763] [Task: sst2] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-06-08:17:44:48,408 WARNING  [task.py:775] [Task: sst2] 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:1491: 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(
+2024-06-08:17:44:55,646 INFO     [task.py:395] Building contexts for winogrande on rank 0...
+100%|██████████| 1267/1267 [00:00<00:00, 69512.79it/s]
+2024-06-08:17:44:55,730 INFO     [task.py:395] Building contexts for sst2 on rank 0...
+100%|██████████| 872/872 [00:00<00:00, 2510.72it/s]
+2024-06-08:17:44:56,105 INFO     [task.py:395] Building contexts for piqa on rank 0...
+100%|██████████| 1838/1838 [00:01<00:00, 1081.99it/s]
+2024-06-08:17:44:57,878 INFO     [task.py:395] Building contexts for mrpc on rank 0...
+100%|██████████| 408/408 [00:00<00:00, 1797.57it/s]
+2024-06-08:17:44:58,123 INFO     [task.py:395] Building contexts for indic_boolq_hi on rank 0...
+100%|██████████| 3270/3270 [00:01<00:00, 3052.08it/s]
+2024-06-08:17:44:59,362 INFO     [task.py:395] Building contexts for indic_arc_easy_hi on rank 0...
+100%|██████████| 2376/2376 [00:02<00:00, 1118.63it/s]
+2024-06-08:17:45:01,729 INFO     [task.py:395] Building contexts for indic_arc_challenge_hi on rank 0...
+100%|██████████| 1172/1172 [00:01<00:00, 1122.96it/s]
+2024-06-08:17:45:02,893 INFO     [task.py:395] Building contexts for copa on rank 0...
+100%|██████████| 100/100 [00:00<00:00, 61990.90it/s]
+2024-06-08:17:45:02,903 INFO     [task.py:395] Building contexts for boolq on rank 0...
+100%|██████████| 3270/3270 [00:01<00:00, 1966.21it/s]
+2024-06-08:17:45:04,697 INFO     [task.py:395] Building contexts for arc_easy on rank 0...
+100%|██████████| 2376/2376 [00:02<00:00, 1054.38it/s]
+2024-06-08:17:45:07,096 INFO     [evaluator.py:379] Running loglikelihood requests
+Token indices sequence length is longer than the specified maximum sequence length for this model (1333 > 1024). Running this sequence through the model will result in indexing errors
+Running loglikelihood requests:   0%|          | 0/45739 [00:00<?, ?it/s]
+Passed argument batch_size = auto:1. Detecting largest batch size
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+
+Running loglikelihood requests: 100%|██████████| 45739/45739 [1:08:05<00:00, 11.20it/s]
+  0%|          | 0/100 [00:00<?, ?it/s]
+
+
+
+100%|██████████| 100/100 [02:14<00:00,  1.34s/it]
+hf (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), 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     |0.4972|±  |0.0141|
+|sst2                  |      1|none  |     0|acc     |0.5069|±  |0.0169|
+|piqa                  |      1|none  |     0|acc     |0.5207|±  |0.0117|
+|                      |       |none  |     0|acc_norm|0.5005|±  |0.0117|
+|mrpc                  |      1|none  |     0|acc     |0.3162|±  |0.0230|
+|                      |       |none  |     0|f1      |0.0000|±  |0.0000|
+|indic_boolq_hi        |      1|none  |     0|acc     |0.6217|±  |0.0085|
+|indic_arc_easy_hi     |      1|none  |     0|acc     |0.2433|±  |0.0088|
+|indic_arc_challenge_hi|      1|none  |     0|acc     |0.2116|±  |0.0119|
+|copa                  |      1|none  |     0|acc     |0.5900|±  |0.0494|
+|boolq                 |      2|none  |     0|acc     |0.3783|±  |0.0085|
+|arc_easy              |      1|none  |     0|acc     |0.2588|±  |0.0090|
+|                      |       |none  |     0|acc_norm|0.2559|±  |0.0090|

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

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venv/lib/python3.10/site-packages/transformers/models/code_llama/__init__.py

@@ -0,0 +1,57 @@
+# Copyright 2023 MetaAI and The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from typing import TYPE_CHECKING
+
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available
+
+
+_import_structure = {}
+
+try:
+    if not is_sentencepiece_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
+    _import_structure["tokenization_code_llama"] = ["CodeLlamaTokenizer"]
+
+try:
+    if not is_tokenizers_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
+    _import_structure["tokenization_code_llama_fast"] = ["CodeLlamaTokenizerFast"]
+
+if TYPE_CHECKING:
+    try:
+        if not is_sentencepiece_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
+        from .tokenization_code_llama import CodeLlamaTokenizer
+
+    try:
+        if not is_tokenizers_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
+        from .tokenization_code_llama_fast import CodeLlamaTokenizerFast
+
+else:
+    import sys
+
+    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)