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+
+2024-05-14:11:44:44,947 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-14:11:44:50,094 INFO     [__main__.py:335] Selected Tasks: ['indiccopa-hi']
+2024-05-14:11:44:50,096 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-14:11:44:50,096 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/data/cronscript/ckpts//hf_ckpt//global_step100'}
+/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/gpu_migration/core/register.py:145: UserWarning: "hpu:X" notation is not supported by Gaudi PyTorch intergration bridge. Please change to "hpu" without index (Triggered internally at /npu-stack/pytorch-integration/pytorch_helpers/lazy_to_backend.cpp:53.)
+  return func(*args, **kwargs)
+/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/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
+  warnings.warn(
+You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
+2024-05-14:11:44:58,445 WARNING  [task.py:763] [Task: indiccopa-hi] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-05-14:11:44:58,446 WARNING  [task.py:775] [Task: indiccopa-hi] metric acc is defined, but higher_is_better is not. using default higher_is_better=True
+[2024-05-14 11:44:58,004] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+/usr/local/lib/python3.10/dist-packages/datasets/load.py:1486: FutureWarning: The repository for ai4bharat/IndicCOPA contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at https://hf.co/datasets/ai4bharat/IndicCOPA
+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(
+2024-05-14:11:44:59,758 WARNING  [task.py:322] [Task: indiccopa-hi] has_training_docs and has_validation_docs are False, using test_docs as fewshot_docs but this is not recommended.
+2024-05-14:11:44:59,759 WARNING  [task.py:322] [Task: indiccopa-hi] has_training_docs and has_validation_docs are False, using test_docs as fewshot_docs but this is not recommended.
+2024-05-14:11:44:59,778 INFO     [task.py:395] Building contexts for indiccopa-hi on rank 3...
+100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 56/56 [00:00<00:00, 109552.72it/s]
+Passed argument batch_size = auto:1. Detecting largest batch size
+2024-05-14:11:45:05,430 INFO     [evaluator.py:379] Running loglikelihood requests
+/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(
+Determined largest batch size: 64

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lm-evaluation-harness/wandb/run-20240514_163424-u68awlcv/files/output.log

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+
+2024-05-14:16:34:25,157 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-14:16:34:30,618 INFO     [__main__.py:335] Selected Tasks: ['indiccopa-hi']
+2024-05-14:16:34:30,621 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-14:16:34:30,621 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/data/cronscript/ckpts//hf_ckpt//global_step100'}
+/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/gpu_migration/core/register.py:145: UserWarning: "hpu:X" notation is not supported by Gaudi PyTorch intergration bridge. Please change to "hpu" without index (Triggered internally at /npu-stack/pytorch-integration/pytorch_helpers/lazy_to_backend.cpp:53.)
+  return func(*args, **kwargs)
+/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(
+[2024-05-14 16:34:41,210] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
+  warnings.warn(
+You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
+2024-05-14:16:34:41,607 WARNING  [task.py:763] [Task: indiccopa-hi] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-05-14:16:34:41,607 WARNING  [task.py:775] [Task: indiccopa-hi] 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 ai4bharat/IndicCOPA contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at https://hf.co/datasets/ai4bharat/IndicCOPA
+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(
+2024-05-14:16:34:42,860 WARNING  [task.py:322] [Task: indiccopa-hi] has_training_docs and has_validation_docs are False, using test_docs as fewshot_docs but this is not recommended.
+2024-05-14:16:34:42,860 WARNING  [task.py:322] [Task: indiccopa-hi] has_training_docs and has_validation_docs are False, using test_docs as fewshot_docs but this is not recommended.
+2024-05-14:16:34:42,879 INFO     [task.py:395] Building contexts for indiccopa-hi on rank 2...
+100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 56/56 [00:00<00:00, 102033.46it/s]
+2024-05-14:16:34:44,718 INFO     [evaluator.py:379] Running loglikelihood requests
+Passed argument batch_size = auto:1. Detecting largest batch size
+Determined largest batch size: 64
+/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(

lm-evaluation-harness/wandb/run-20240514_163424-u68awlcv/files/requirements.txt

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lm-evaluation-harness/wandb/run-20240522_185312-zyl3j05r/files/config.yaml

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+_wandb:
+  desc: null
+  value:
+    python_version: 3.10.12
+    cli_version: 0.17.0
+    framework: huggingface
+    huggingface_version: 4.41.0
+    is_jupyter_run: false
+    is_kaggle_kernel: false
+    start_time: 1716403992
+    t:
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lm-evaluation-harness/wandb/run-20240522_185312-zyl3j05r/files/output.log

@@ -0,0 +1,34 @@
+
+2024-05-22:18:53:13,321 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-22:18:53:21,821 INFO     [__main__.py:335] Selected Tasks: ['arc_easy', 'hellaswag', 'mrpc', 'openbookqa', 'sst2', 'winogrande']
+2024-05-22:18:53:21,822 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-22:18:53:21,823 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/mnt/weka/peacock/experiments/llama/checkpoint/llamav2-3b//hf_ckpt//global_step12000'}
+2024-05-22:18:53:24,119 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_step12000 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_step12000/tree/main' for available files.

lm-evaluation-harness/wandb/run-20240522_185312-zyl3j05r/files/requirements.txt

@@ -0,0 +1,155 @@
+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
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+      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
+    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/llamav2-3b/hf/global_step20000,tokenizer=huggyllama/llama-13b
+    batch_size: auto
+    batch_sizes:
+    - 64
+    device: null
+    use_cache: null
+    limit: null
+    bootstrap_iters: 100000
+    gen_kwargs: null

lm-evaluation-harness/wandb/run-20240529_130519-xd9jvj0r/files/media/table/evaluation/eval_results_1_00813995c90417288110.table.json

@@ -0,0 +1 @@
+{"columns": ["Tasks", "Version", "Filter", "num_fewshot", "Metric", "Value", "Stderr"], "data": [["winogrande", 1.0, "none", 0, "acc", "0.5098658247829518", "0.0140"], ["sst2", 1.0, "none", 0, "acc", "0.518348623853211", "0.0169"], ["piqa", 1.0, "none", 0, "acc", "0.528835690968444", "0.0116"], ["piqa", 1.0, "none", 0, "acc_norm", "0.5", "0.0117"], ["mrpc", 1.0, "none", 0, "acc", "0.5098039215686274", "0.0248"], ["mrpc", 1.0, "none", 0, "f1", "0.601593625498008", "0.0258"], ["copa", 1.0, "none", 0, "acc", "0.69", "0.0465"], ["boolq", 2.0, "none", 0, "acc", "0.4709480122324159", "0.0087"], ["arc_easy", 1.0, "none", 0, "acc", "0.24705387205387205", "0.0089"], ["arc_easy", 1.0, "none", 0, "acc_norm", "0.25084175084175087", "0.0089"]]}

lm-evaluation-harness/wandb/run-20240529_130519-xd9jvj0r/files/output.log

@@ -0,0 +1,492 @@
+
+2024-05-29:13:05:20,470 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-29:13:05:29,765 INFO     [__main__.py:335] Selected Tasks: ['arc_easy', 'boolq', 'copa', 'mrpc', 'piqa', 'sst2', 'winogrande']
+2024-05-29:13:05:29,766 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-29:13:05:29,767 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/mnt/weka/peacock/experiments/llama/eval/checkpoint/llamav2-3b/hf/global_step20000', 'tokenizer': 'huggyllama/llama-13b'}
+2024-05-29:13:05:32,474 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, 17.1MB/s]
+Downloading data: 100%|██████████| 331k/331k [00:00<00:00, 2.52MB/s]
+Downloading data: 100%|██████████| 346k/346k [00:00<00:00, 4.35MB/s]
+Downloading data: 100%|██████████| 86.1k/86.1k [00:00<00:00, 1.09MB/s]
+Generating train split: 100%|██████████| 2251/2251 [00:00<00:00, 53472.84 examples/s]
+Generating test split: 100%|██████████| 2376/2376 [00:00<00:00, 329149.73 examples/s]
+Generating validation split: 100%|██████████| 570/570 [00:00<00:00, 190832.80 examples/s]
+2024-05-29:13:06:03,624 WARNING  [task.py:763] [Task: boolq] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-05-29:13:06:03,625 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, 39.1MB/s]
+Downloading readme: 100%|██████████| 18.2k/18.2k [00:00<00:00, 32.5MB/s]
+Downloading data: 100%|██████████| 4.12M/4.12M [00:00<00:00, 46.2MB/s]
+Generating train split: 100%|██████████| 9427/9427 [00:00<00:00, 22200.60 examples/s]
+Generating validation split: 100%|██████████| 3270/3270 [00:00<00:00, 21763.04 examples/s]
+Generating test split: 100%|██████████| 3245/3245 [00:00<00:00, 23211.76 examples/s]
+2024-05-29:13:06:07,477 WARNING  [task.py:763] [Task: copa] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-05-29:13:06:07,478 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, 50.9MB/s]
+Generating train split: 100%|██████████| 400/400 [00:00<00:00, 16080.60 examples/s]
+Generating validation split: 100%|██████████| 100/100 [00:00<00:00, 12116.66 examples/s]
+Generating test split: 100%|██████████| 500/500 [00:00<00:00, 17103.27 examples/s]
+2024-05-29:13:06:09,591 WARNING  [task.py:763] [Task: mrpc] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-05-29:13:06:09,592 WARNING  [task.py:775] [Task: mrpc] metric acc is defined, but higher_is_better is not. using default higher_is_better=True
+2024-05-29:13:06:09,592 WARNING  [task.py:763] [Task: mrpc] metric f1 is defined, but aggregation is not. using default aggregation=f1
+2024-05-29:13:06:09,593 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, 36.4MB/s]
+Downloading data: 100%|██████████| 649k/649k [00:00<00:00, 4.35MB/s]
+Downloading data: 100%|██████████| 75.7k/75.7k [00:00<00:00, 514kB/s]
+Downloading data: 100%|██████████| 308k/308k [00:00<00:00, 2.07MB/s]
+Generating train split: 100%|██████████| 3668/3668 [00:00<00:00, 412524.99 examples/s]
+Generating validation split: 100%|██████████| 408/408 [00:00<00:00, 174211.14 examples/s]
+Generating test split: 100%|██████████| 1725/1725 [00:00<00:00, 381220.00 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, 17.5MB/s]
+Downloading data: 100%|██████████| 1.82M/1.82M [00:00<00:00, 4.13MB/s]
+Downloading data: 100%|██████████| 815k/815k [00:00<00:00, 18.8MB/s]
+Generating train split: 100%|██████████| 16113/16113 [00:00<00:00, 23724.07 examples/s]
+Generating test split: 100%|██████████| 3084/3084 [00:00<00:00, 24526.51 examples/s]
+Generating validation split: 100%|██████████| 1838/1838 [00:00<00:00, 23691.90 examples/s]
+2024-05-29:13:06:20,348 WARNING  [task.py:763] [Task: sst2] metric acc is defined, but aggregation is not. using default aggregation=mean
+2024-05-29:13:06:20,350 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, 20.2MB/s]
+Downloading data: 100%|██████████| 72.8k/72.8k [00:00<00:00, 506kB/s]
+Downloading data: 100%|██████████| 148k/148k [00:00<00:00, 997kB/s]
+Generating train split: 100%|██████████| 67349/67349 [00:00<00:00, 1424390.02 examples/s]
+Generating validation split: 100%|██████████| 872/872 [00:00<00:00, 401695.01 examples/s]
+Generating test split: 100%|██████████| 1821/1821 [00:00<00:00, 538140.46 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, 12.4MB/s]
+Downloading readme: 100%|██████████| 9.97k/9.97k [00:00<00:00, 20.0MB/s]
+Downloading data: 100%|██████████| 3.40M/3.40M [00:00<00:00, 6.92MB/s]
+Generating train split: 100%|██████████| 40398/40398 [00:01<00:00, 23997.77 examples/s]
+Generating test split: 100%|██████████| 1767/1767 [00:00<00:00, 24340.56 examples/s]
+Generating validation split: 100%|██████████| 1267/1267 [00:00<00:00, 23383.30 examples/s]
+2024-05-29:13:06:33,010 INFO     [task.py:395] Building contexts for winogrande on rank 0...
+100%|██████████| 1267/1267 [00:00<00:00, 69363.08it/s]
+2024-05-29:13:06:33,095 INFO     [task.py:395] Building contexts for sst2 on rank 0...
+100%|██████████| 872/872 [00:00<00:00, 2561.80it/s]
+2024-05-29:13:06:33,465 INFO     [task.py:395] Building contexts for piqa on rank 0...
+100%|██████████| 1838/1838 [00:01<00:00, 1074.86it/s]
+2024-05-29:13:06:35,248 INFO     [task.py:395] Building contexts for mrpc on rank 0...
+100%|██████████| 408/408 [00:00<00:00, 1825.85it/s]
+2024-05-29:13:06:35,493 INFO     [task.py:395] Building contexts for copa on rank 0...
+100%|██████████| 100/100 [00:00<00:00, 62341.02it/s]
+2024-05-29:13:06:35,502 INFO     [task.py:395] Building contexts for boolq on rank 0...
+100%|██████████| 3270/3270 [00:01<00:00, 1978.21it/s]
+2024-05-29:13:06:37,286 INFO     [task.py:395] Building contexts for arc_easy on rank 0...
+100%|██████████| 2376/2376 [00:02<00:00, 1069.99it/s]
+2024-05-29:13:06:39,656 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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+bootstrapping for stddev: f1_score
+
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+
+100%|██████████| 100/100 [02:10<00:00,  1.31s/it]
+hf (pretrained=/mnt/weka/peacock/experiments/llama/eval/checkpoint/llamav2-3b/hf/global_step20000,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     |0.5099|±  |0.0140|
+|sst2      |      1|none  |     0|acc     |0.5183|±  |0.0169|
+|piqa      |      1|none  |     0|acc     |0.5288|±  |0.0116|
+|          |       |none  |     0|acc_norm|0.5000|±  |0.0117|
+|mrpc      |      1|none  |     0|acc     |0.5098|±  |0.0248|
+|          |       |none  |     0|f1      |0.6016|±  |0.0258|
+|copa      |      1|none  |     0|acc     |0.6900|±  |0.0465|
+|boolq     |      2|none  |     0|acc     |0.4709|±  |0.0087|
+|arc_easy  |      1|none  |     0|acc     |0.2471|±  |0.0089|
+|          |       |none  |     0|acc_norm|0.2508|±  |0.0089|

lm-evaluation-harness/wandb/run-20240529_130519-xd9jvj0r/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
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lm-evaluation-harness/wandb/run-20240529_130623-ufhzqpyv/files/wandb-summary.json

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+{"winogrande/alias": "winogrande", "sst2/alias": "sst2", "piqa/alias": "piqa", "mrpc/alias": "mrpc", "copa/alias": "copa", "boolq/alias": "boolq", "arc_easy/alias": "arc_easy", "winogrande/acc": 0.5146014206787688, "winogrande/acc_stderr": 0.014046492383275828, "sst2/acc": 0.5114678899082569, "sst2/acc_stderr": 0.016937396972070192, "piqa/acc": 0.5223068552774756, "piqa/acc_stderr": 0.011654208652596466, "piqa/acc_norm": 0.5, "piqa/acc_norm_stderr": 0.011665824165343952, "mrpc/acc": 0.5416666666666666, "mrpc/acc_stderr": 0.024697874098492393, "mrpc/f1": 0.6326129666011788, "mrpc/f1_stderr": 0.025050723379674043, "copa/acc": 0.63, "copa/acc_stderr": 0.048523658709391, "boolq/acc": 0.4960244648318043, "boolq/acc_stderr": 0.008744778542942208, "arc_easy/acc": 0.24705387205387205, "arc_easy/acc_stderr": 0.008850055161459234, "arc_easy/acc_norm": 0.25757575757575757, "arc_easy/acc_norm_stderr": 0.00897318782021522, "_timestamp": 1716990757.7724519, "_runtime": 2773.994240760803, "_step": 1, "evaluation/eval_results": {"_type": "table-file", "sha256": "6095a22fc5c6735d359daca7fe5a1486a6c9c87db26599b4c3595bb14c307524", "size": 744, "artifact_path": "wandb-client-artifact://ax08pg8v3hz4eo8g18rr3xaw4o5r0epznushfyofy212s8wkdegthhpzanc68d1wlsteysc23hmztj2nq46qt9gxf1a6m2hdgrgqwvkxk7fgte0qow1e1r5cnw96kexl/evaluation/eval_results.table.json", "_latest_artifact_path": "wandb-client-artifact://kcnumnwra23haddpkb9l17rw0dtnptb9yz8p77h4uogsbihbjsjrjczia1dwm4v3f7h9uolsotajwuzk9rbozea84m0z1bdd5cs335000qygbqw9ajwa4ii5c1e0zgvu:latest/evaluation/eval_results.table.json", "path": "media/table/evaluation/eval_results_1_6095a22fc5c6735d359d.table.json", "ncols": 7, "nrows": 10}, "_wandb": {"runtime": 2773}}

lm-evaluation-harness/wandb/run-20240530_064617-5iiwti0v/files/config.yaml

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+    cli_version: 0.17.0
+    framework: huggingface
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+    is_kaggle_kernel: false
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lm-evaluation-harness/wandb/run-20240530_064617-5iiwti0v/files/output.log

@@ -0,0 +1,38 @@
+
+2024-05-30:06:46:18,181 INFO     [__main__.py:251] Verbosity set to INFO
+2024-05-30:06:46:27,642 INFO     [__main__.py:335] Selected Tasks: ['arc_easy', 'boolq', 'copa', 'mrpc', 'piqa', 'sst2', 'winogrande']
+2024-05-30:06:46:27,643 INFO     [evaluator.py:131] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234
+2024-05-30:06:46:27,644 INFO     [evaluator.py:177] Initializing hf model, with arguments: {'pretrained': '/mnt/weka/peacock/experiments/llama/eval/checkpoint-english/llamav2-3b/hf/global_step20000', 'tokenizer': '/mnt/weka/peacock/tokenization/trained-tokenizer/enhiben_50k/'}
+2024-05-30:06:46:29,944 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_064617-5iiwti0v/files/requirements.txt

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+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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+certifi==2024.2.2
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+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
+huggingface-hub==0.23.2
+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
+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
+setuptools==59.6.0
+setuptools==69.5.1
+six==1.16.0
+smmap==5.0.1
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+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
+transformers==4.36.2
+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