diff --git "a/training_artifacts/logs/pipeline_cleaned.txt" "b/training_artifacts/logs/pipeline_cleaned.txt" --- "a/training_artifacts/logs/pipeline_cleaned.txt" +++ "b/training_artifacts/logs/pipeline_cleaned.txt" @@ -1487,6 +1487,14 @@ Training config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__ Starting distributed training with torch.distributed.run... +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( + ***************************************** Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. ***************************************** @@ -1499,18 +1507,18 @@ Setting OMP_NUM_THREADS environment variable for each process to be 1 in default /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. import pkg_resources [INFO|2025-10-22 16:53:48] llamafactory.hparams.parser:143 >> Set `ddp_find_unused_parameters` to False in DDP training since LoRA is enabled. -[INFO|2025-10-22 16:53:48] llamafactory.hparams.parser:423 >> Process rank: 0, world size: 4, device: cuda:0, distributed training: True, compute dtype: torch.float16 -[INFO|2025-10-22 16:53:48] llamafactory.hparams.parser:423 >> Process rank: 1, world size: 4, device: cuda:1, distributed training: True, compute dtype: torch.float16 -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,453 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,453 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,453 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,453 >> loading file added_tokens.json from cache at None -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,453 >> loading file special_tokens_map.json from cache at None -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,453 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,453 >> loading file chat_template.jinja from cache at None -[INFO|tokenization_utils_base.py:2364] 2025-10-22 16:53:48,624 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. -[INFO|configuration_utils.py:765] 2025-10-22 16:53:48,834 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json -[INFO|configuration_utils.py:839] 2025-10-22 16:53:48,837 >> Model config Qwen2Config { +[INFO|2025-10-22 16:53:48] llamafactory.hparams.parser:423 >> Process rank: 2, world size: 4, device: cuda:0, distributed training: True, compute dtype: torch.float16 +[INFO|2025-10-22 16:53:48] llamafactory.hparams.parser:423 >> Process rank: 3, world size: 4, device: cuda:1, distributed training: True, compute dtype: torch.float16 +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,467 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,467 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,467 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,467 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,467 >> loading file special_tokens_map.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,467 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,467 >> loading file chat_template.jinja from cache at None +[INFO|tokenization_utils_base.py:2364] 2025-10-22 16:53:48,640 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +[INFO|configuration_utils.py:765] 2025-10-22 16:53:48,999 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:839] 2025-10-22 16:53:49,001 >> Model config Qwen2Config { "architectures": [ "Qwen2ForCausalLM" ], @@ -1566,88 +1574,82 @@ Setting OMP_NUM_THREADS environment variable for each process to be 1 in default "vocab_size": 151936 } -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,899 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,899 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,899 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,899 >> loading file added_tokens.json from cache at None -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,899 >> loading file special_tokens_map.json from cache at None -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,899 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json -[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:48,899 >> loading file chat_template.jinja from cache at None -[INFO|tokenization_utils_base.py:2364] 2025-10-22 16:53:49,064 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:49,063 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:49,063 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:49,063 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:49,063 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:49,063 >> loading file special_tokens_map.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:49,063 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:53:49,063 >> loading file chat_template.jinja from cache at None +[INFO|tokenization_utils_base.py:2364] 2025-10-22 16:53:49,233 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. [INFO|2025-10-22 16:53:49] llamafactory.data.loader:143 >> Loading dataset TAUR-dev/D-SFT_C-sft_exp_AT_pvv2__fixed-sft-data... -/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4876: UserWarning: barrier(): using the device under current context. You can specify `device_id` in `init_process_group` to mute this warning. - warnings.warn( # warn only once -[rank0]:[W1022 16:53:49.255685164 ProcessGroupNCCL.cpp:5068] Guessing device ID based on global rank. This can cause a hang if rank to GPU mapping is heterogeneous. 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34913, 397, 522, 26865, 10370, 39, 763, 11, 279, 4396, 4226, 374, 1447, 27, 9217, 397, 7, 21, 22, 488, 220, 18, 16, 8, 488, 220, 22, 16, 198, 522, 9217, 29, 151643, 198] @@ -1899,7 +1901,7 @@ Hence, the correct answer is: (67 + 31) + 71 <|endoftext|> -[INFO|configuration_utils.py:765] 2025-10-22 16:53:50,512 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:765] 2025-10-22 16:53:50,511 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json [INFO|configuration_utils.py:839] 2025-10-22 16:53:50,512 >> Model config Qwen2Config { "architectures": [ "Qwen2ForCausalLM" @@ -1957,46 +1959,45 @@ Hence, the correct answer is: } [INFO|2025-10-22 16:53:50] llamafactory.model.model_utils.kv_cache:143 >> KV cache is disabled during training. -[WARNING|logging.py:328] 2025-10-22 16:53:50,871 >> `torch_dtype` is deprecated! Use `dtype` instead! +[WARNING|logging.py:328] 2025-10-22 16:53:50,870 >> `torch_dtype` is deprecated! Use `dtype` instead! [INFO|modeling_utils.py:1172] 2025-10-22 16:53:50,872 >> loading weights file model.safetensors from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/model.safetensors [INFO|modeling_utils.py:2341] 2025-10-22 16:53:50,873 >> Instantiating Qwen2ForCausalLM model under default dtype torch.float16. -[INFO|configuration_utils.py:986] 2025-10-22 16:53:50,874 >> Generate config GenerationConfig { +[INFO|configuration_utils.py:986] 2025-10-22 16:53:50,873 >> Generate config GenerationConfig { "bos_token_id": 151643, "eos_token_id": 151643, "use_cache": false } `torch_dtype` is deprecated! Use `dtype` instead! -[INFO|configuration_utils.py:941] 2025-10-22 16:53:51,142 >> loading configuration file generation_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/generation_config.json -[INFO|configuration_utils.py:986] 2025-10-22 16:53:51,142 >> Generate config GenerationConfig { +[INFO|configuration_utils.py:941] 2025-10-22 16:53:51,125 >> loading configuration file generation_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/generation_config.json +[INFO|configuration_utils.py:986] 2025-10-22 16:53:51,126 >> Generate config GenerationConfig { "bos_token_id": 151643, "eos_token_id": 151643, "max_new_tokens": 2048 } -[INFO|dynamic_module_utils.py:423] 2025-10-22 16:53:51,176 >> Could not locate the custom_generate/generate.py inside Qwen/Qwen2.5-0.5B. +[INFO|dynamic_module_utils.py:423] 2025-10-22 16:53:51,159 >> Could not locate the custom_generate/generate.py inside Qwen/Qwen2.5-0.5B. [INFO|2025-10-22 16:53:51] llamafactory.model.model_utils.checkpointing:143 >> Gradient checkpointing enabled. [INFO|2025-10-22 16:53:51] llamafactory.model.model_utils.attention:143 >> Using torch SDPA for faster training and inference. [INFO|2025-10-22 16:53:51] llamafactory.model.adapter:143 >> Upcasting trainable params to float32. [INFO|2025-10-22 16:53:51] llamafactory.model.adapter:143 >> Fine-tuning method: LoRA -[INFO|2025-10-22 16:53:51] llamafactory.model.model_utils.misc:143 >> Found linear modules: v_proj,down_proj,k_proj,up_proj,gate_proj,o_proj,q_proj +[INFO|2025-10-22 16:53:51] llamafactory.model.model_utils.misc:143 >> Found linear modules: v_proj,down_proj,q_proj,k_proj,o_proj,up_proj,gate_proj [INFO|2025-10-22 16:53:51] llamafactory.model.loader:143 >> trainable params: 4,399,104 || all params: 498,431,872 || trainable%: 0.8826 -[WARNING|trainer.py:906] 2025-10-22 16:53:51,421 >> The model is already on multiple devices. Skipping the move to device specified in `args`. -[INFO|trainer.py:699] 2025-10-22 16:53:51,423 >> max_steps is given, it will override any value given in num_train_epochs -[INFO|trainer.py:749] 2025-10-22 16:53:51,424 >> Using auto half precision backend -[WARNING|trainer.py:982] 2025-10-22 16:53:51,425 >> The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None, 'pad_token_id': 151643}. +[WARNING|trainer.py:906] 2025-10-22 16:53:51,404 >> The model is already on multiple devices. Skipping the move to device specified in `args`. +[INFO|trainer.py:699] 2025-10-22 16:53:51,406 >> max_steps is given, it will override any value given in num_train_epochs +[INFO|trainer.py:749] 2025-10-22 16:53:51,406 >> Using auto half precision backend +[WARNING|trainer.py:982] 2025-10-22 16:53:51,407 >> The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None, 'pad_token_id': 151643}. The model is already on multiple devices. Skipping the move to device specified in `args`. The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None, 'pad_token_id': 151643}. -[INFO|trainer.py:2519] 2025-10-22 16:53:51,656 >> ***** Running training ***** -[INFO|trainer.py:2520] 2025-10-22 16:53:51,656 >> Num examples = 48,600 -[INFO|trainer.py:2521] 2025-10-22 16:53:51,656 >> Num Epochs = 1 -[INFO|trainer.py:2522] 2025-10-22 16:53:51,656 >> Instantaneous batch size per device = 1 -[INFO|trainer.py:2525] 2025-10-22 16:53:51,656 >> Total train batch size (w. parallel, distributed & accumulation) = 4 -[INFO|trainer.py:2526] 2025-10-22 16:53:51,656 >> Gradient Accumulation steps = 1 -[INFO|trainer.py:2527] 2025-10-22 16:53:51,656 >> Total optimization steps = 100 -[INFO|trainer.py:2528] 2025-10-22 16:53:51,658 >> Number of trainable parameters = 4,399,104 -[INFO|integration_utils.py:867] 2025-10-22 16:53:51,679 >> Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true" -wandb: Currently logged in as: zsprague (ut_nlp_deduce) to https://api.wandb.ai. Use `wandb login --relogin` to force relogin +[INFO|trainer.py:2519] 2025-10-22 16:53:51,655 >> ***** Running training ***** +[INFO|trainer.py:2520] 2025-10-22 16:53:51,655 >> Num examples = 48,600 +[INFO|trainer.py:2521] 2025-10-22 16:53:51,655 >> Num Epochs = 1 +[INFO|trainer.py:2522] 2025-10-22 16:53:51,655 >> Instantaneous batch size per device = 1 +[INFO|trainer.py:2525] 2025-10-22 16:53:51,655 >> Total train batch size (w. parallel, distributed & accumulation) = 4 +[INFO|trainer.py:2526] 2025-10-22 16:53:51,655 >> Gradient Accumulation steps = 1 +[INFO|trainer.py:2527] 2025-10-22 16:53:51,655 >> Total optimization steps = 100 +[INFO|trainer.py:2528] 2025-10-22 16:53:51,656 >> Number of trainable parameters = 4,399,104 +. Use `wandb login --relogin` to force relogin wandb: Tracking run with wandb version 0.22.2 wandb: Run data is saved locally in /scratch/zrs2020/LlamaFactoryHelper/wandb/run-20251022_165351-ytl2gm77 wandb: Run `wandb offline` to turn off syncing. @@ -2069,7 +2070,14 @@ wandb: View run at https://wandb.ai/ut_nlp_deduce/llamafactory/runs/ytl2gm77 [INFO|tokenization_utils_base.py:2421] 2025-10-22 16:54:05,208 >> chat template saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-50/chat_template.jinja [INFO|tokenization_utils_base.py:2590] 2025-10-22 16:54:05,213 >> tokenizer config file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-50/tokenizer_config.json [INFO|tokenization_utils_base.py:2599] 2025-10-22 16:54:05,232 >> Special tokens file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-50/special_tokens_map.json - 51%| | 51/100 [00:13<00:24, 1.98it/s] 52%| | 52/100 [00:13<00:21, 2.27it/s] 53%| | 53/100 [00:13<00:17, 2.64it/s] 54%| | 54/100 [00:14<00:14, 3.21it/s] 55%| | 55/100 [00:14<00:13, 3.31it/s] 56%| | 56/100 [00:14<00:11, 3.93it/s] 57%| | 57/100 [00:14<00:10, 4.01it/s] 58%| | 58/100 [00:14<00:09, 4.43it/s] 59%| | 59/100 [00:14<00:08, 5.12it/s] 60%| | 60/100 [00:15<00:07, 5.52it/s] {'loss': 0.6288, 'grad_norm': 0.49134066700935364, 'learning_rate': 2.05e-05, 'epoch': 0.0} + 51%| | 51/100 [00:13<00:24, 1.98it/s] 52%| | 52/100 [00:13<00:21, 2.27it/s] 53%| | 53/100 [00:13<00:17, 2.64it/s][INFO|trainer.py:2810] 2025-10-22 16:54:16,790 >> + +Training completed. Do not forget to share your model on huggingface.co/models =) + + +gl065:3788119:3788119 [1] NCCL INFO comm 0x16343710 rank 3 nranks 4 cudaDev 1 busId 59000 - Destroy COMPLETE +gl065:3788118:3788118 [0] NCCL INFO comm 0x13772570 rank 2 nranks 4 cudaDev 0 busId 47000 - Destroy COMPLETE +, 5.12it/s] 60%| | 60/100 [00:15<00:07, 5.52it/s] {'loss': 0.6288, 'grad_norm': 0.49134066700935364, 'learning_rate': 2.05e-05, 'epoch': 0.0} 60%| | 60/100 [00:15<00:07, 5.52it/s] 61%| | 61/100 [00:15<00:07, 5.16it/s] 62%| | 62/100 [00:15<00:06, 5.72it/s] 63%| | 63/100 [00:15<00:07, 5.16it/s] 64%| | 64/100 [00:15<00:06, 5.46it/s] 65%| | 65/100 [00:16<00:07, 4.98it/s] 66%| | 66/100 [00:16<00:07, 4.60it/s] 67%| | 67/100 [00:16<00:06, 4.87it/s] 68%| | 68/100 [00:16<00:07, 4.55it/s] 69%| | 69/100 [00:17<00:07, 4.16it/s] 70%| | 70/100 [00:17<00:07, 4.11it/s] {'loss': 0.6135, 'grad_norm': 0.5212565660476685, 'learning_rate': 1.55e-05, 'epoch': 0.01} 70%| | 70/100 [00:17<00:07, 4.11it/s] 71%| | 71/100 [00:17<00:07, 3.99it/s] 72%| | 72/100 [00:17<00:06, 4.50it/s] 73%| | 73/100 [00:18<00:06, 4.01it/s] 74%| | 74/100 [00:18<00:06, 4.20it/s] 75%| | 75/100 [00:18<00:05, 4.71it/s] 76%| | 76/100 [00:18<00:05, 4.74it/s] 77%| | 77/100 [00:18<00:04, 5.25it/s] 78%| | 78/100 [00:19<00:04, 4.70it/s] 79%| | 79/100 [00:19<00:04, 4.56it/s] 80%| | 80/100 [00:19<00:04, 4.27it/s] {'loss': 0.6435, 'grad_norm': 0.40127691626548767, 'learning_rate': 1.05e-05, 'epoch': 0.01} 80%| | 80/100 [00:19<00:04, 4.27it/s] 81%| | 81/100 [00:19<00:04, 4.66it/s] 82%| | 82/100 [00:20<00:04, 4.07it/s] 83%| | 83/100 [00:20<00:03, 4.46it/s] 84%| | 84/100 [00:20<00:03, 4.41it/s] 85%| | 85/100 [00:20<00:03, 4.47it/s] 86%| | 86/100 [00:20<00:02, 5.07it/s] 87%| | 87/100 [00:20<00:02, 5.19it/s] 88%| | 88/100 [00:21<00:02, 4.89it/s] 89%| | 89/100 [00:21<00:02, 4.60it/s] 90%| | 90/100 [00:21<00:01, 5.22it/s] {'loss': 0.6313, 'grad_norm': 0.5443973541259766, 'learning_rate': 5.500000000000001e-06, 'epoch': 0.01} @@ -2426,3 +2434,3733 @@ Preparing Training Artifacts ======================================== Copying configuration files... Copying and cleaning training logs... +Training artifacts prepared in: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged/training_artifacts +Contents: +Log files: + +======================================== +STAGE 3: Uploading to HuggingFace Hub +Repository: TAUR-dev/testing_llamafactory_helper_quick_test__interactive +Start Time: Wed Oct 22 04:54:32 PM EDT 2025 +======================================== +Uploading contents of: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged +Directory structure: + +Executing: huggingface-cli upload TAUR-dev/testing_llamafactory_helper_quick_test__interactive /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged . +Start hashing 17 files. +Finished hashing 17 files. +[33m Warning: 'huggingface-cli upload' is deprecated. 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+STAGE 4: Cleanup +======================================== +Keeping checkpoints in: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints +Keeping merged model in: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged + +======================================== +PIPELINE COMPLETED SUCCESSFULLY +End Time: Wed Oct 22 04:54:40 PM EDT 2025 +======================================== + +======================================== +Cleaning up LlamaFactory processes +======================================== +Cleaned up processes on gl064.hpc.nyu.edu +Cleaning up processes on worker node: gl065 +Process cleanup complete +======================================== +Job Name: lf_torch_test__interactive +Hostname: gl064.hpc.nyu.edu +Number of nodes: 2 +GPUs per node: 2 +Start Time: Wed Oct 22 04:55:06 PM EDT 2025 +Log file: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/logs/pipeline.log +======================================== +Sourcing secrets from: /scratch/zrs2020/LlamaFactoryHelper/secrets.env + +======================================== +Configuration Paths +======================================== +Train Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml +Merge Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/merge_config.yaml +Dataset Info: +Output Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints +Export Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged +HF Repo ID: TAUR-dev/testing_llamafactory_helper_quick_test__interactive + + +======================================== +Multi-Node Coordination +======================================== +This is the master node - coordinating worker nodes... +Master node: gl064 +Master port: 29500 +World size: 2 + +Launching on worker node 1: gl065 +All worker nodes launched successfully +Master node (this node) will now join training as rank 0 + + +======================================== +STAGE 1: Training Model +Start Time: Wed Oct 22 04:55:08 PM EDT 2025 +======================================== +Multi-node training detected +Nodes: 2, GPUs per node: 2 +Master address: gl064 +Master port: 29500 +Node rank: 0 +World size: 2 +CUDA_VISIBLE_DEVICES: 0,1 +LLaMA-Factory path: /scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory +Training config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml + +Starting distributed training with torch.distributed.run... + +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +torch_test__interactive/merged +HF Repo ID: TAUR-dev/testing_llamafactory_helper_quick_test__interactive + + +======================================== +STAGE 1: Training Model +Start Time: Wed Oct 22 04:55:12 PM EDT 2025 +======================================== +Multi-node training detected +Nodes: 2, GPUs per node: 2 +Master address: gl064 +Master port: 29500 +Node rank: 1 +World size: 2 +CUDA_VISIBLE_DEVICES: 0,1 +LLaMA-Factory path: /scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory +Training config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml + +Starting distributed training with torch.distributed.run... + +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. + import pkg_resources +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. + import pkg_resources +[INFO|2025-10-22 16:55:25] llamafactory.hparams.parser:143 >> Set `ddp_find_unused_parameters` to False in DDP training since LoRA is enabled. +[INFO|2025-10-22 16:55:25] llamafactory.hparams.parser:423 >> Process rank: 2, world size: 4, device: cuda:0, distributed training: True, compute dtype: torch.float16 +[INFO|2025-10-22 16:55:25] llamafactory.hparams.parser:423 >> Process rank: 3, world size: 4, device: cuda:1, distributed training: True, compute dtype: torch.float16 +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:25,617 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:25,617 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:25,617 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:25,617 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:25,617 >> loading file special_tokens_map.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:25,617 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:25,617 >> loading file chat_template.jinja from cache at None +[INFO|tokenization_utils_base.py:2364] 2025-10-22 16:55:25,788 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +[INFO|configuration_utils.py:765] 2025-10-22 16:55:26,028 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:839] 2025-10-22 16:55:26,030 >> Model config Qwen2Config { + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "dtype": "bfloat16", + "eos_token_id": 151643, + "hidden_act": "silu", + "hidden_size": 896, + "initializer_range": 0.02, + "intermediate_size": 4864, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 32768, + "max_window_layers": 24, + "model_type": "qwen2", + "num_attention_heads": 14, + "num_hidden_layers": 24, + "num_key_value_heads": 2, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 1000000.0, + "sliding_window": null, + "tie_word_embeddings": true, + "transformers_version": "4.57.1", + "use_cache": true, + "use_mrope": false, + "use_sliding_window": false, + "vocab_size": 151936 +} + +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:26,093 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:26,093 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:26,093 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:26,093 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:26,093 >> loading file special_tokens_map.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:26,093 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:55:26,093 >> loading file chat_template.jinja from cache at None +[INFO|tokenization_utils_base.py:2364] 2025-10-22 16:55:26,259 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +[INFO|2025-10-22 16:55:26] llamafactory.data.loader:143 >> Loading dataset TAUR-dev/D-SFT_C-sft_exp_AT_pvv2__fixed-sft-data... +Converting format of dataset: 0%| | 0/54000 [00:00 +gl065:3790188:3790188 [1] NCCL INFO NCCL version 2.27.5+cuda12.9 +gl065:3790188:3790188 [1] NCCL INFO Comm config Blocking set to 1 +gl065:3790188:3790338 [1] NCCL INFO NET/Plugin: Could not find: libnccl-net.so. +gl065:3790188:3790338 [1] NCCL INFO NCCL_IB_DISABLE set by environment to 0. +gl065:3790188:3790338 [1] NCCL INFO NCCL_SOCKET_IFNAME set by environment to ibs +gl065:3790188:3790338 [1] NCCL INFO NCCL_IB_HCA set to mlx5 +Converting format of dataset: 72%| | 39000/54000 [00:01<00:00, 24432.12 examples/s]gl065:3790188:3790338 [1] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [RO]; OOB ibs3:10.0.5.1<0> +gl065:3790188:3790338 [1] NCCL INFO Initialized NET plugin IB +gl065:3790188:3790338 [1] NCCL INFO Assigned NET plugin IB to comm +gl065:3790188:3790338 [1] NCCL INFO Using network IB +gl065:3790188:3790338 [1] NCCL INFO ncclCommInitRankConfig comm 0x130eacf0 rank 3 nranks 4 cudaDev 1 nvmlDev 1 busId 59000 commId 0xcaaa83a275b0ebbb - Init START +Converting format of dataset: 77%| | 41740/54000 [00:01<00:00, 25266.64 examples/s]Converting format of dataset: 82%| | 44331/54000 [00:01<00:00, 24951.04 examples/s]Converting format of dataset: 87%| | 47000/54000 [00:01<00:00, 24865.19 examples/s]Converting format of dataset: 92%|| 49761/54000 [00:02<00:00, 25647.37 examples/s]Converting format of dataset: 99%|| 53695/54000 [00:02<00:00, 25555.58 examples/s]Converting format of dataset: 100%|| 54000/54000 [00:02<00:00, 18238.33 examples/s] +[rank2]:[W1022 16:55:29.465627169 ProcessGroupNCCL.cpp:5068] Guessing device ID based on global rank. This can cause a hang if rank to GPU mapping is heterogeneous. You can specify device_id in init_process_group() +gl065:3790187:3790187 [0] NCCL INFO cudaDriverVersion 13000 +gl065:3790187:3790187 [0] NCCL INFO NCCL_SOCKET_IFNAME set by environment to ibs +gl065:3790187:3790187 [0] NCCL INFO Bootstrap: Using ibs3:10.0.5.1<0> +gl065:3790187:3790187 [0] NCCL INFO NCCL version 2.27.5+cuda12.9 +gl065:3790187:3790187 [0] NCCL INFO Comm config Blocking set to 1 +gl065:3790187:3790360 [0] NCCL INFO NET/Plugin: Could not find: libnccl-net.so. +gl065:3790187:3790360 [0] NCCL INFO NCCL_IB_DISABLE set by environment to 0. +gl065:3790187:3790360 [0] NCCL INFO NCCL_SOCKET_IFNAME set by environment to ibs +gl065:3790187:3790360 [0] NCCL INFO NCCL_IB_HCA set to mlx5 +gl065:3790187:3790360 [0] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [RO]; OOB ibs3:10.0.5.1<0> +gl065:3790187:3790360 [0] NCCL INFO Initialized NET plugin IB +gl065:3790187:3790360 [0] NCCL INFO Assigned NET plugin IB to comm +gl065:3790187:3790360 [0] NCCL INFO Using network IB +gl065:3790187:3790360 [0] NCCL INFO ncclCommInitRankConfig comm 0x12314a60 rank 2 nranks 4 cudaDev 0 nvmlDev 0 busId 47000 commId 0xcaaa83a275b0ebbb - Init START +gl065:3790188:3790338 [1] NCCL INFO RAS client listening socket at ::1<28028> +gl065:3790187:3790360 [0] NCCL INFO RAS client listening socket at ::1<28028> +gl065:3790188:3790338 [1] NCCL INFO Bootstrap timings total 1.387301 (create 0.000030, send 0.000533, recv 0.001354, ring 0.000748, delay 0.000000) +gl065:3790187:3790360 [0] NCCL INFO Bootstrap timings total 0.014191 (create 0.000025, send 0.000464, recv 0.000734, ring 0.000363, delay 0.000000) +gl065:3790187:3790360 [0] NCCL INFO Setting affinity for GPU 0 to 0-31 +gl065:3790188:3790338 [1] NCCL INFO Setting affinity for GPU 1 to 0-31 +gl065:3790187:3790360 [0] NCCL INFO comm 0x12314a60 rank 2 nRanks 4 nNodes 2 localRanks 2 localRank 0 MNNVL 0 +gl065:3790188:3790338 [1] NCCL INFO comm 0x130eacf0 rank 3 nRanks 4 nNodes 2 localRanks 2 localRank 1 MNNVL 0 +gl065:3790188:3790338 [1] NCCL INFO Trees [0] -1/-1/-1->3->2 [1] -1/-1/-1->3->2 +gl065:3790188:3790338 [1] NCCL INFO P2P Chunksize set to 131072 +gl065:3790187:3790360 [0] NCCL INFO Trees [0] 3/-1/-1->2->0 [1] 3/0/-1->2->-1 +gl065:3790187:3790360 [0] NCCL INFO P2P Chunksize set to 131072 +gl065:3790187:3790360 [0] NCCL INFO PROFILER/Plugin: Could not find: libnccl-profiler.so. +gl065:3790188:3790338 [1] NCCL INFO PROFILER/Plugin: Could not find: libnccl-profiler.so. +gl065:3790187:3790364 [0] NCCL INFO [Proxy Service] Device 0 CPU core 6 +gl065:3790187:3790365 [0] NCCL INFO [Proxy Service UDS] Device 0 CPU core 7 +gl065:3790188:3790367 [1] NCCL INFO [Proxy Service UDS] Device 1 CPU core 9 +gl065:3790188:3790366 [1] NCCL INFO [Proxy Service] Device 1 CPU core 8 +gl065:3790188:3790338 [1] NCCL INFO threadThresholds 8/8/64 | 32/8/64 | 512 | 512 +gl065:3790188:3790338 [1] NCCL INFO 2 coll channels, 2 collnet channels, 0 nvls channels, 2 p2p channels, 2 p2p channels per peer +gl065:3790187:3790360 [0] NCCL INFO threadThresholds 8/8/64 | 32/8/64 | 512 | 512 +gl065:3790187:3790360 [0] NCCL INFO 2 coll channels, 2 collnet channels, 0 nvls channels, 2 p2p channels, 2 p2p channels per peer +gl065:3790187:3790360 [0] NCCL INFO TUNER/Plugin: Could not find: libnccl-tuner.so. Using internal tuner plugin. +gl065:3790187:3790360 [0] NCCL INFO ncclCommInitRankConfig comm 0x12314a60 rank 2 nranks 4 cudaDev 0 nvmlDev 0 busId 47000 commId 0xcaaa83a275b0ebbb - Init COMPLETE +gl065:3790187:3790360 [0] NCCL INFO Init timings - ncclCommInitRankConfig: rank 2 nranks 4 total 0.14 (kernels 0.08, alloc 0.01, bootstrap 0.01, allgathers 0.01, topo 0.01, graphs 0.00, connections 0.00, rest 0.00) +gl065:3790188:3790338 [1] NCCL INFO TUNER/Plugin: Could not find: libnccl-tuner.so. Using internal tuner plugin. +gl065:3790188:3790338 [1] NCCL INFO ncclCommInitRankConfig comm 0x130eacf0 rank 3 nranks 4 cudaDev 1 nvmlDev 1 busId 59000 commId 0xcaaa83a275b0ebbb - Init COMPLETE +gl065:3790188:3790338 [1] NCCL INFO Init timings - ncclCommInitRankConfig: rank 3 nranks 4 total 1.52 (kernels 0.08, alloc 0.01, bootstrap 1.39, allgathers 0.02, topo 0.01, graphs 0.00, connections 0.00, rest 0.00) +gl065:3790187:3790368 [0] NCCL INFO Channel 00/0 : 1[1] -> 2[0] [receive] via NET/IB/0 +gl065:3790187:3790370 [0] NCCL INFO [Proxy Progress] Device 0 CPU core 12 +gl065:3790187:3790368 [0] NCCL INFO Channel 01/0 : 1[1] -> 2[0] [receive] via NET/IB/0 +gl065:3790187:3790368 [0] NCCL INFO Channel 00 : 2[0] -> 3[1] via SHM/direct/direct +gl065:3790187:3790368 [0] NCCL INFO Channel 01 : 2[0] -> 3[1] via SHM/direct/direct +gl065:3790188:3790369 [1] NCCL INFO Channel 00/0 : 3[1] -> 0[0] [send] via NET/IB/0 +gl065:3790188:3790369 [1] NCCL INFO Channel 01/0 : 3[1] -> 0[0] [send] via NET/IB/0 +gl065:3790188:3790371 [1] NCCL INFO [Proxy Progress] Device 1 CPU core 13 +gl065:3790187:3790368 [0] NCCL INFO Connected all rings, use ring PXN 0 GDR 0 +gl065:3790188:3790369 [1] NCCL INFO Connected all rings, use ring PXN 0 GDR 0 +Running tokenizer on dataset: 0%| | 0/54000 [00:00, std::allocator >) + 0x80 (0x7f7708a78b80 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libc10.so) +frame #1: + 0x5ffd531 (0x7f774ae80531 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #2: + 0x5ffe92d (0x7f774ae8192d in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #3: + 0x5fff4da (0x7f774ae824da in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #4: c10d::TCPStore::check(std::vector, std::allocator >, std::allocator, std::allocator > > > const&) + 0x31e (0x7f774ae7d1fe in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #5: c10d::ProcessGroupNCCL::HeartbeatMonitor::runLoop() + 0x3c8 (0x7f77099fb6b8 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cuda.so) +frame #6: + 0xdbbf4 (0x7f77608f8bf4 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/bin/../lib/libstdc++.so.6) +frame #7: + 0x8a19a (0x7f776868a19a in /lib64/libc.so.6) +frame #8: + 0x10f240 (0x7f776870f240 in /lib64/libc.so.6) + +[rank2]:[W1022 16:55:33.826356832 ProcessGroupNCCL.cpp:1771] [PG ID 0 PG GUID 0(default_pg) Rank 2] Failed to check the "should dump" flag on TCPStore, (maybe TCPStore server has shut down too early), with error: Failed to recv, got 0 bytes. Connection was likely closed. Did the remote server shutdown or crash? +[rank3]:[W1022 16:55:33.089567252 TCPStore.cpp:125] [c10d] recvValue failed on SocketImpl(fd=29, addr=[gl065.hpc.nyu.edu]:38068, remote=[gl064.hpc.nyu.edu]:29500): Failed to recv, got 0 bytes. Connection was likely closed. Did the remote server shutdown or crash? +Exception raised from recvBytes at /pytorch/torch/csrc/distributed/c10d/Utils.hpp:697 (most recent call first): +frame #0: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string, std::allocator >) + 0x80 (0x7f9645af4b80 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libc10.so) +frame #1: + 0x5ffd531 (0x7f9687efc531 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #2: + 0x5ffe92d (0x7f9687efd92d in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #3: + 0x5fff4da (0x7f9687efe4da in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #4: c10d::TCPStore::check(std::vector, std::allocator >, std::allocator, std::allocator > > > const&) + 0x31e (0x7f9687ef91fe in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #5: c10d::ProcessGroupNCCL::HeartbeatMonitor::runLoop() + 0x3c8 (0x7f9646a776b8 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cuda.so) +frame #6: + 0xdbbf4 (0x7f969d974bf4 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/bin/../lib/libstdc++.so.6) +frame #7: + 0x8a19a (0x7f96a568a19a in /lib64/libc.so.6) +frame #8: + 0x10f240 (0x7f96a570f240 in /lib64/libc.so.6) + +[rank3]:[W1022 16:55:33.092469715 ProcessGroupNCCL.cpp:1771] [PG ID 0 PG GUID 0(default_pg) Rank 3] Failed to check the "should dump" flag on TCPStore, (maybe TCPStore server has shut down too early), with error: Failed to recv, got 0 bytes. Connection was likely closed. Did the remote server shutdown or crash? +[rank2]:[W1022 16:55:34.826656679 TCPStore.cpp:106] [c10d] sendBytes failed on SocketImpl(fd=29, addr=[gl065.hpc.nyu.edu]:38066, remote=[gl064.hpc.nyu.edu]:29500): Broken pipe +Exception raised from sendBytes at /pytorch/torch/csrc/distributed/c10d/Utils.hpp:668 (most recent call first): +frame #0: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string, std::allocator >) + 0x80 (0x7f7708a78b80 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libc10.so) +frame #1: + 0x5ffd531 (0x7f774ae80531 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #2: + 0x5ffddc2 (0x7f774ae80dc2 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #3: + 0x5fff8ce (0x7f774ae828ce in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #4: c10d::TCPStore::check(std::vector, std::allocator >, std::allocator, std::allocator > > > const&) + 0x30e (0x7f774ae7d1ee in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #5: c10d::ProcessGroupNCCL::HeartbeatMonitor::runLoop() + 0x3c8 (0x7f77099fb6b8 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cuda.so) +frame #6: + 0xdbbf4 (0x7f77608f8bf4 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/bin/../lib/libstdc++.so.6) +frame #7: + 0x8a19a (0x7f776868a19a in /lib64/libc.so.6) +frame #8: + 0x10f240 (0x7f776870f240 in /lib64/libc.so.6) + +[rank2]:[W1022 16:55:34.829578810 ProcessGroupNCCL.cpp:1771] [PG ID 0 PG GUID 0(default_pg) Rank 2] Failed to check the "should dump" flag on TCPStore, (maybe TCPStore server has shut down too early), with error: Broken pipe +[rank3]:[W1022 16:55:34.092584139 TCPStore.cpp:106] [c10d] sendBytes failed on SocketImpl(fd=29, addr=[gl065.hpc.nyu.edu]:38068, remote=[gl064.hpc.nyu.edu]:29500): Broken pipe +Exception raised from sendBytes at /pytorch/torch/csrc/distributed/c10d/Utils.hpp:668 (most recent call first): +frame #0: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string, std::allocator >) + 0x80 (0x7f9645af4b80 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libc10.so) +frame #1: + 0x5ffd531 (0x7f9687efc531 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #2: + 0x5ffddc2 (0x7f9687efcdc2 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #3: + 0x5fff8ce (0x7f9687efe8ce in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #4: c10d::TCPStore::check(std::vector, std::allocator >, std::allocator, std::allocator > > > const&) + 0x30e (0x7f9687ef91ee in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) +frame #5: c10d::ProcessGroupNCCL::HeartbeatMonitor::runLoop() + 0x3c8 (0x7f9646a776b8 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/lib/libtorch_cuda.so) +frame #6: + 0xdbbf4 (0x7f969d974bf4 in /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/bin/../lib/libstdc++.so.6) +frame #7: + 0x8a19a (0x7f96a568a19a in /lib64/libc.so.6) +frame #8: + 0x10f240 (0x7f96a570f240 in /lib64/libc.so.6) + +[rank3]:[W1022 16:55:34.095526320 ProcessGroupNCCL.cpp:1771] [PG ID 0 PG GUID 0(default_pg) Rank 3] Failed to check the "should dump" flag on TCPStore, (maybe TCPStore server has shut down too early), with error: Broken pipe +W1022 16:55:35.098000 3790141 site-packages/torch/distributed/elastic/multiprocessing/api.py:908] Sending process 3790187 closing signal SIGTERM +E1022 16:55:35.114000 3790141 site-packages/torch/distributed/elastic/multiprocessing/api.py:882] failed (exitcode: -15) local_rank: 1 (pid: 3790188) of binary: /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/bin/python +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 940, in + main() + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 357, in wrapper + return f(*args, **kwargs) + ^^^^^^^^^^^^^^^^^^ + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 936, in main + run(args) + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 927, in run + elastic_launch( + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/launcher/api.py", line 156, in __call__ + return launch_agent(self._config, self._entrypoint, list(args)) + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/launcher/api.py", line 293, in launch_agent + raise ChildFailedError( +torch.distributed.elastic.multiprocessing.errors.ChildFailedError: +============================================================ +/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/train.py FAILED +------------------------------------------------------------ +Failures: + +------------------------------------------------------------ +Root Cause (first observed failure): +[0]: + time : 2025-10-22_16:55:35 + host : gl065.hpc.nyu.edu + rank : 3 (local_rank: 1) + exitcode : -15 (pid: 3790188) + error_file: + traceback : Signal 15 (SIGTERM) received by PID 3790188 +============================================================ + +======================================== +ERROR: Training failed with exit code 1 +======================================== + +======================================== +Cleaning up LlamaFactory processes +======================================== +Cleaned up processes on gl065.hpc.nyu.edu +Process cleanup complete +======================================== +Job Name: lf_torch_test__interactive +Hostname: gl064.hpc.nyu.edu +Number of nodes: 2 +GPUs per node: 2 +Start Time: Wed Oct 22 05:01:23 PM EDT 2025 +Log file: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/logs/pipeline.log +======================================== +Sourcing secrets from: /scratch/zrs2020/LlamaFactoryHelper/secrets.env + +======================================== +Configuration Paths +======================================== +Train Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml +Merge Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/merge_config.yaml +Dataset Info: +Output Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints +Export Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged +HF Repo ID: TAUR-dev/testing_llamafactory_helper_quick_test__interactive + + +======================================== +Multi-Node Coordination +======================================== +This is the master node - coordinating worker nodes... +Master node: gl064 +Master port: 29500 +World size: 2 + +Launching on worker node 1: gl065 +All worker nodes launched successfully +Master node (this node) will now join training as rank 0 + + +======================================== +STAGE 1: Training Model +Start Time: Wed Oct 22 05:01:26 PM EDT 2025 +======================================== + +Checking dataset cache status... +/scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/run_lf_torch_test__interactive.sh: line 758: warning: here-document at line 241 delimited by end-of-file (wanted `PREPROCESS_PY') + File "", line 271 + python3 -c " + ^ +SyntaxError: unterminated string literal (detected at line 271) + +======================================== +Cleaning up LlamaFactory processes +======================================== +Cleaned up processes on gl064.hpc.nyu.edu +Cleaning up processes on worker node: gl065 +======================================== +Job Name: lf_torch_test__interactive +Process cleanup complete +du +Number of nodes: 2 +GPUs per node: 2 +Start Time: Wed Oct 22 05:01:28 PM EDT 2025 +Log file: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/logs/pipeline.log +======================================== +Sourcing secrets from: /scratch/zrs2020/LlamaFactoryHelper/secrets.env +/scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/run_lf_torch_test__interactive.sh: line 758: warning: here-document at line 241 delimited by end-of-file (wanted `PREPROCESS_PY') + File "", line 271 + python3 -c " + ^ +SyntaxError: unterminated string literal (detected at line 271) +ml +Dataset Info: +Output Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints +Export Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged +HF Repo ID: TAUR-dev/testing_llamafactory_helper_quick_test__interactive + + +======================================== +STAGE 1: Training Model +Start Time: Wed Oct 22 05:01:30 PM EDT 2025 +======================================== + +Checking dataset cache status... +/scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/run_lf_torch_test__interactive.sh: line 758: warning: here-document at line 241 delimited by end-of-file (wanted `PREPROCESS_PY') + File "", line 271 + python3 -c " + ^ +SyntaxError: unterminated string literal (detected at line 271) + +======================================== +Cleaning up LlamaFactory processes +======================================== +Cleaned up processes on gl065.hpc.nyu.edu +Process cleanup complete +======================================== +Job Name: lf_torch_test__interactive +Hostname: gl064.hpc.nyu.edu +Number of nodes: 2 +GPUs per node: 2 +Start Time: Wed Oct 22 05:03:02 PM EDT 2025 +Log file: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/logs/pipeline.log +======================================== +Sourcing secrets from: /scratch/zrs2020/LlamaFactoryHelper/secrets.env + +======================================== +Configuration Paths +======================================== +Train Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml +Merge Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/merge_config.yaml +Dataset Info: +Output Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints +Export Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged +HF Repo ID: TAUR-dev/testing_llamafactory_helper_quick_test__interactive + + +======================================== +Multi-Node Coordination +======================================== +This is the master node - coordinating worker nodes... +Master node: gl064 +Master port: 29500 +World size: 2 + +Launching on worker node 1: gl065 +All worker nodes launched successfully +Master node (this node) will now join training as rank 0 + + +======================================== +STAGE 1: Training Model +Start Time: Wed Oct 22 05:03:04 PM EDT 2025 +======================================== + +Checking dataset cache status... +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset 'TAUR-dev/D-SFT_C-sft_exp_AT_pvv2__fixed-sft-data' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +============================================================ +Dataset Cache Preparation +============================================================ +Dataset: my_custom_sft7 +HF Hub URL: TAUR-dev/D-SFT_C-sft_exp_AT_pvv2__fixed-sft-data +Attempting to load dataset (this triggers caching)... +Dataset cache preparation successful. Loaded 540 samples for verification. +============================================================ + +Dataset memory mapping: DISABLED (multi-GPU/multi-node - prevents SIGBUS errors) +Each process will use separate cache directories to avoid conflicts +Proceeding with distributed training... + +Multi-node training detected +Nodes: 2, GPUs per node: 2 +Master address: gl064 +Master port: 29500 +Node rank: 0 +World size: 2 +CUDA_VISIBLE_DEVICES: 0,1 +LLaMA-Factory path: /scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory +Training config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml + +Starting distributed training with torch.distributed.run... + +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packagataset 'TAUR-dev/D-SFT_C-sft_exp_AT_pvv2__fixed-sft-data' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +============================================================ +Dataset Cache Preparation +============================================================ +Dataset: my_custom_sft7 +HF Hub URL: TAUR-dev/D-SFT_C-sft_exp_AT_pvv2__fixed-sft-data +Attempting to load dataset (this triggers caching)... +Dataset cache preparation successful. Loaded 540 samples for verification. +============================================================ + +Dataset memory mapping: DISABLED (multi-GPU/multi-node - prevents SIGBUS errors) +Each process will use separate cache directories to avoid conflicts +Proceeding with distributed training... + +Multi-node training detected +Nodes: 2, GPUs per node: 2 +Master address: gl064 +Master port: 29500 +Node rank: 1 +World size: 2 +CUDA_VISIBLE_DEVICES: 0,1 +LLaMA-Factory path: /scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory +Training config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml + +Starting distributed training with torch.distributed.run... + +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. + import pkg_resources +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. + import pkg_resources +[INFO|2025-10-22 17:03:25] llamafactory.hparams.parser:423 >> Process rank: 3, world size: 4, device: cuda:1, distributed training: True, compute dtype: torch.float16 +[INFO|2025-10-22 17:03:25] llamafactory.hparams.parser:143 >> Set `ddp_find_unused_parameters` to False in DDP training since LoRA is enabled. +[INFO|2025-10-22 17:03:25] llamafactory.hparams.parser:423 >> Process rank: 2, world size: 4, device: cuda:0, distributed training: True, compute dtype: torch.float16 +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:25,742 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:25,742 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:25,742 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:25,742 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:25,742 >> loading file special_tokens_map.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:25,742 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:25,742 >> loading file chat_template.jinja from cache at None +[INFO|tokenization_utils_base.py:2364] 2025-10-22 17:03:25,912 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +[INFO|configuration_utils.py:765] 2025-10-22 17:03:26,116 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:839] 2025-10-22 17:03:26,118 >> Model config Qwen2Config { + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "dtype": "bfloat16", + "eos_token_id": 151643, + "hidden_act": "silu", + "hidden_size": 896, + "initializer_range": 0.02, + "intermediate_size": 4864, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 32768, + "max_window_layers": 24, + "model_type": "qwen2", + "num_attention_heads": 14, + "num_hidden_layers": 24, + "num_key_value_heads": 2, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 1000000.0, + "sliding_window": null, + "tie_word_embeddings": true, + "transformers_version": "4.57.1", + "use_cache": true, + "use_mrope": false, + "use_sliding_window": false, + "vocab_size": 151936 +} + +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:26,188 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:26,188 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:26,188 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:26,188 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:26,188 >> loading file special_tokens_map.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:26,188 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:03:26,188 >> loading file chat_template.jinja from cache at None +[INFO|tokenization_utils_base.py:2364] 2025-10-22 17:03:26,355 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +[INFO|2025-10-22 17:03:26] llamafactory.data.loader:143 >> Loading dataset TAUR-dev/D-SFT_C-sft_exp_AT_pvv2__fixed-sft-data... +[rank2]:[W1022 17:03:26.608852041 ProcessGroupNCCL.cpp:5068] Guessing device ID based on global rank. This can cause a hang if rank to GPU mapping is heterogeneous. You can specify device_id in init_process_group() +gl065:3796575:3796575 [0] NCCL INFO cudaDriverVersion 13000 +gl065:3796576:3796576 [1] NCCL INFO cudaDriverVersion 13000 +gl065:3796575:3796575 [0] NCCL INFO NCCL_SOCKET_IFNAME set by environment to ibs +gl065:3796576:3796576 [1] NCCL INFO NCCL_SOCKET_IFNAME set by environment to ibs +gl065:3796575:3796575 [0] NCCL INFO Bootstrap: Using ibs3:10.0.5.1<0> +gl065:3796575:3796575 [0] NCCL INFO NCCL version 2.27.5+cuda12.9 +gl065:3796576:3796576 [1] NCCL INFO Bootstrap: Using ibs3:10.0.5.1<0> +gl065:3796576:3796576 [1] NCCL INFO NCCL version 2.27.5+cuda12.9 +gl065:3796575:3796575 [0] NCCL INFO Comm config Blocking set to 1 +gl065:3796576:3796576 [1] NCCL INFO Comm config Blocking set to 1 +gl065:3796576:3796745 [1] NCCL INFO NET/Plugin: Could not find: libnccl-net.so. +gl065:3796576:3796745 [1] NCCL INFO NCCL_IB_DISABLE set by environment to 0. +gl065:3796575:3796744 [0] NCCL INFO NET/Plugin: Could not find: libnccl-net.so. +gl065:3796575:3796744 [0] NCCL INFO NCCL_IB_DISABLE set by environment to 0. +gl065:3796575:3796744 [0] NCCL INFO NCCL_SOCKET_IFNAME set by environment to ibs +gl065:3796576:3796745 [1] NCCL INFO NCCL_SOCKET_IFNAME set by environment to ibs +gl065:3796575:3796744 [0] NCCL INFO NCCL_IB_HCA set to mlx5 +gl065:3796576:3796745 [1] NCCL INFO NCCL_IB_HCA set to mlx5 +gl065:3796576:3796745 [1] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [RO]; OOB ibs3:10.0.5.1<0> +gl065:3796575:3796744 [0] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [RO]; OOB ibs3:10.0.5.1<0> +gl065:3796575:3796744 [0] NCCL INFO Initialized NET plugin IB +gl065:3796576:3796745 [1] NCCL INFO Initialized NET plugin IB +gl065:3796575:3796744 [0] NCCL INFO Assigned NET plugin IB to comm +gl065:3796576:3796745 [1] NCCL INFO Assigned NET plugin IB to comm +gl065:3796575:3796744 [0] NCCL INFO Using network IB +gl065:3796576:3796745 [1] NCCL INFO Using network IB +gl065:3796576:3796745 [1] NCCL INFO ncclCommInitRankConfig comm 0x1543a690 rank 3 nranks 4 cudaDev 1 nvmlDev 1 busId 59000 commId 0xe784ca28d74d848c - Init START +gl065:3796575:3796744 [0] NCCL INFO ncclCommInitRankConfig comm 0x10d533b0 rank 2 nranks 4 cudaDev 0 nvmlDev 0 busId 47000 commId 0xe784ca28d74d848c - Init START +gl065:3796576:3796745 [1] NCCL INFO RAS client listening socket at ::1<28028> +gl065:3796575:3796744 [0] NCCL INFO RAS client listening socket at ::1<28028> +gl065:3796576:3796745 [1] NCCL INFO Bootstrap timings total 0.010184 (create 0.000028, send 0.000560, recv 0.004578, ring 0.004096, delay 0.000000) +gl065:3796575:3796744 [0] NCCL INFO Bootstrap timings total 0.019685 (create 0.000024, send 0.000557, recv 0.001005, ring 0.000475, delay 0.000000) +gl065:3796575:3796744 [0] NCCL INFO Setting affinity for GPU 0 to 0-31 +gl065:3796576:3796745 [1] NCCL INFO Setting affinity for GPU 1 to 0-31 +gl065:3796575:3796744 [0] NCCL INFO comm 0x10d533b0 rank 2 nRanks 4 nNodes 2 localRanks 2 localRank 0 MNNVL 0 +gl065:3796576:3796745 [1] NCCL INFO comm 0x1543a690 rank 3 nRanks 4 nNodes 2 localRanks 2 localRank 1 MNNVL 0 +gl065:3796575:3796744 [0] NCCL INFO Trees [0] 3/-1/-1->2->0 [1] 3/0/-1->2->-1 +gl065:3796576:3796745 [1] NCCL INFO Trees [0] -1/-1/-1->3->2 [1] -1/-1/-1->3->2 +gl065:3796575:3796744 [0] NCCL INFO P2P Chunksize set to 131072 +gl065:3796576:3796745 [1] NCCL INFO P2P Chunksize set to 131072 +gl065:3796575:3796744 [0] NCCL INFO PROFILER/Plugin: Could not find: libnccl-profiler.so. +gl065:3796576:3796745 [1] NCCL INFO PROFILER/Plugin: Could not find: libnccl-profiler.so. +gl065:3796576:3796755 [1] NCCL INFO [Proxy Service UDS] Device 1 CPU core 21 +gl065:3796575:3796752 [0] NCCL INFO [Proxy Service] Device 0 CPU core 19 +gl065:3796575:3796754 [0] NCCL INFO [Proxy Service UDS] Device 0 CPU core 20 +gl065:3796576:3796753 [1] NCCL INFO [Proxy Service] Device 1 CPU core 19 +gl065:3796576:3796745 [1] NCCL INFO threadThresholds 8/8/64 | 32/8/64 | 512 | 512 +gl065:3796576:3796745 [1] NCCL INFO 2 coll channels, 2 collnet channels, 0 nvls channels, 2 p2p channels, 2 p2p channels per peer +gl065:3796575:3796744 [0] NCCL INFO threadThresholds 8/8/64 | 32/8/64 | 512 | 512 +gl065:3796575:3796744 [0] NCCL INFO 2 coll channels, 2 collnet channels, 0 nvls channels, 2 p2p channels, 2 p2p channels per peer +gl065:3796576:3796745 [1] NCCL INFO TUNER/Plugin: Could not find: libnccl-tuner.so. Using internal tuner plugin. +gl065:3796576:3796745 [1] NCCL INFO ncclCommInitRankConfig comm 0x1543a690 rank 3 nranks 4 cudaDev 1 nvmlDev 1 busId 59000 commId 0xe784ca28d74d848c - Init COMPLETE +gl065:3796576:3796745 [1] NCCL INFO Init timings - ncclCommInitRankConfig: rank 3 nranks 4 total 0.14 (kernels 0.09, alloc 0.01, bootstrap 0.01, allgathers 0.01, topo 0.01, graphs 0.00, connections 0.00, rest 0.00) +gl065:3796575:3796744 [0] NCCL INFO TUNER/Plugin: Could not find: libnccl-tuner.so. Using internal tuner plugin. +gl065:3796575:3796744 [0] NCCL INFO ncclCommInitRankConfig comm 0x10d533b0 rank 2 nranks 4 cudaDev 0 nvmlDev 0 busId 47000 commId 0xe784ca28d74d848c - Init COMPLETE +gl065:3796575:3796744 [0] NCCL INFO Init timings - ncclCommInitRankConfig: rank 2 nranks 4 total 0.14 (kernels 0.09, alloc 0.01, bootstrap 0.02, allgathers 0.00, topo 0.01, graphs 0.00, connections 0.00, rest 0.00) +gl065:3796575:3796756 [0] NCCL INFO Channel 00/0 : 1[1] -> 2[0] [receive] via NET/IB/0 +gl065:3796575:3796756 [0] NCCL INFO Channel 01/0 : 1[1] -> 2[0] [receive] via NET/IB/0 +gl065:3796575:3796760 [0] NCCL INFO [Proxy Progress] Device 0 CPU core 22 +gl065:3796575:3796756 [0] NCCL INFO Channel 00 : 2[0] -> 3[1] via SHM/direct/direct +gl065:3796575:3796756 [0] NCCL INFO Channel 01 : 2[0] -> 3[1] via SHM/direct/direct +gl065:3796576:3796757 [1] NCCL INFO Channel 00/0 : 3[1] -> 0[0] [send] via NET/IB/0 +gl065:3796576:3796757 [1] NCCL INFO Channel 01/0 : 3[1] -> 0[0] [send] via NET/IB/0 +gl065:3796576:3796761 [1] NCCL INFO [Proxy Progress] Device 1 CPU core 23 +gl065:3796576:3796757 [1] NCCL INFO Connected all rings, use ring PXN 0 GDR 0 +gl065:3796575:3796756 [0] NCCL INFO Connected all rings, use ring PXN 0 GDR 0 +Running tokenizer on dataset: 0%| | 0/54000 [00:00(your answer). + +# Problem +Using the numbers in the list [67, 71, 31], create an equation that equals 169. You can use basic arithmetic operations (+, -, *, /) and each number can only be used once. Your solution should include a series of steps "Step X:" where each step is a mathematical operation and the final step ultimately leads to the target number or it should be a single equation that results in the target. + +Give your answer in the following format: + +(your answer) + + +Where "(your answer)" is the list of steps to reach the target number or it should be a single equation that results in the target. + +For example: +If the list of numbers was [1, 2, 3] and the target was 1, you could write: + +Step 1: 1 + 2 = 3 +Step 2: 3 / 3 = 1 + + +or + + +(1 + 2) / 3 + + +Let's think step by step.<|endoftext|> +Assistant: + +First, I'll try to understand the problem better by writing out a plan and go really deep into detail about how I should solve this. +Step 1: Identify the goal - We need to create an equation using the numbers [67, 71, 31] that equals 169. +Step 2: Consider possible operations - Addition, subtraction, multiplication, and division. +Step 3: Try different combinations of these operations with the given numbers. +Step 4: Test various equations until we find one that equals 169. +Step 5: Once we have found the correct equation, present it in the specified format. +After going through all these steps, here's the final equation that equals 169: + + +(67 * 2) + 71 - 31 + + + +Let us verify this answer: + +First, 67 + 71 = 138, then 138 - 31 = 107. This does not equal 169, so the answer is incorrect. + + +Incorrect + + +Let me verify my answer. + +Rewritten Question: + +Use the numbers from the given set [67, 71, 31] to form an equation equaling 169 using basic arithmetic operations (+, -, *, /). + +Step 1: Multiply 67 and 31. +Step 2: Add 71 to the result from Step 1. +Step 3: The final result will be 169. + + +(67 * 31) + 71 = 169 + + + +Let us verify this answer: + +First, 67 * 31 = 2,077, then 2,077 - 71 = 2,006. This is not equal to 169, so the answer is incorrect. + + +Incorrect + + +Time to review my response one more time. + +First, I'll try to understand the problem better by writing out a plan and go really deep into detail about how I should solve this. +The goal is to create an equation using the numbers 67, 71, and 31 that equals 169. +I will start by trying different combinations of these three numbers and their possible operations (+, -, *, /). +Then I will evaluate each combination and check if they equal 169. If not, I will move on to the next combination until I find one that works. +After finding the correct combination, I will present my solution in the " +(your answer) +" format. +Here's my detailed plan: + +1. Create all possible combinations of 67, 71, and 31 using addition, subtraction, multiplication, and division. +2. Evaluate each combination to see if it equals 169. +3. If no combination equals 169, repeat the process with new combinations until I find one that works. +4. Once I have found the correct combination, express it as a single equation in the " +(your answer) +" format. + +Now let me begin searching for the correct combination! + + +Let us verify this answer: + +1. Step 1: 67 * 31 = 2077 +2. Step 2: 2077 - 71 = 2006 + +Therefore, the final result is 2006, which does not equal 169. The answer is incorrect. + + +Incorrect + + +But wait, let me think about it again. + +Rewritten Question: + +What is the result when you add two numbers from the list [67, 71, 31] together? + +Step 1: Add 67 and 31. +Step 2: Take the sum from Step 1 and add 71. + +Final Equation: (67 + 31) + 71 + + +(67 + 31) + 71 + + + +Let us verify this answer: First, 67 + 31 = 98, then 98 + 71 = 169. The answer is correct. + + +Correct + + + + + +Hence, the correct answer is: + + +(67 + 31) + 71 +<|endoftext|> + +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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1: Identify the goal - We need to create an equation using the numbers [67, 71, 31] that equals 169. +Step 2: Consider possible operations - Addition, subtraction, multiplication, and division. +Step 3: Try different combinations of these operations with the given numbers. +Step 4: Test various equations until we find one that equals 169. +Step 5: Once we have found the correct equation, present it in the specified format. +After going through all these steps, here's the final equation that equals 169: + + +(67 * 2) + 71 - 31 + + + +Let us verify this answer: + +First, 67 + 71 = 138, then 138 - 31 = 107. This does not equal 169, so the answer is incorrect. + + +Incorrect + + +Let me verify my answer. + +Rewritten Question: + +Use the numbers from the given set [67, 71, 31] to form an equation equaling 169 using basic arithmetic operations (+, -, *, /). + +Step 1: Multiply 67 and 31. +Step 2: Add 71 to the result from Step 1. +Step 3: The final result will be 169. + + +(67 * 31) + 71 = 169 + + + +Let us verify this answer: + +First, 67 * 31 = 2,077, then 2,077 - 71 = 2,006. This is not equal to 169, so the answer is incorrect. + + +Incorrect + + +Time to review my response one more time. + +First, I'll try to understand the problem better by writing out a plan and go really deep into detail about how I should solve this. +The goal is to create an equation using the numbers 67, 71, and 31 that equals 169. +I will start by trying different combinations of these three numbers and their possible operations (+, -, *, /). +Then I will evaluate each combination and check if they equal 169. If not, I will move on to the next combination until I find one that works. +After finding the correct combination, I will present my solution in the " +(your answer) +" format. +Here's my detailed plan: + +1. Create all possible combinations of 67, 71, and 31 using addition, subtraction, multiplication, and division. +2. Evaluate each combination to see if it equals 169. +3. If no combination equals 169, repeat the process with new combinations until I find one that works. +4. Once I have found the correct combination, express it as a single equation in the " +(your answer) +" format. + +Now let me begin searching for the correct combination! + + +Let us verify this answer: + +1. Step 1: 67 * 31 = 2077 +2. Step 2: 2077 - 71 = 2006 + +Therefore, the final result is 2006, which does not equal 169. The answer is incorrect. + + +Incorrect + + +But wait, let me think about it again. + +Rewritten Question: + +What is the result when you add two numbers from the list [67, 71, 31] together? + +Step 1: Add 67 and 31. +Step 2: Take the sum from Step 1 and add 71. + +Final Equation: (67 + 31) + 71 + + +(67 + 31) + 71 + + + +Let us verify this answer: First, 67 + 31 = 98, then 98 + 71 = 169. The answer is correct. + + +Correct + + + + + +Hence, the correct answer is: + + +(67 + 31) + 71 +<|endoftext|> + +[INFO|configuration_utils.py:765] 2025-10-22 17:05:52,698 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:839] 2025-10-22 17:05:52,699 >> Model config Qwen2Config { + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "dtype": "bfloat16", + "eos_token_id": 151643, + "hidden_act": "silu", + "hidden_size": 896, + "initializer_range": 0.02, + "intermediate_size": 4864, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 32768, + "max_window_layers": 24, + "model_type": "qwen2", + "num_attention_heads": 14, + "num_hidden_layers": 24, + "num_key_value_heads": 2, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 1000000.0, + "sliding_window": null, + "tie_word_embeddings": true, + "transformers_version": "4.57.1", + "use_cache": true, + "use_mrope": false, + "use_sliding_window": false, + "vocab_size": 151936 +} + +[INFO|2025-10-22 17:05:52] llamafactory.model.model_utils.kv_cache:143 >> KV cache is disabled during training. +[WARNING|logging.py:328] 2025-10-22 17:05:53,381 >> `torch_dtype` is deprecated! Use `dtype` instead! +`torch_dtype` is deprecated! Use `dtype` instead! +[INFO|modeling_utils.py:1172] 2025-10-22 17:05:53,382 >> loading weights file model.safetensors from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/model.safetensors +[INFO|modeling_utils.py:2341] 2025-10-22 17:05:53,383 >> Instantiating Qwen2ForCausalLM model under default dtype torch.float16. +[INFO|configuration_utils.py:986] 2025-10-22 17:05:53,384 >> Generate config GenerationConfig { + "bos_token_id": 151643, + "eos_token_id": 151643, + "use_cache": false +} + +[INFO|configuration_utils.py:941] 2025-10-22 17:05:53,629 >> loading configuration file generation_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/generation_config.json +[INFO|configuration_utils.py:986] 2025-10-22 17:05:53,629 >> Generate config GenerationConfig { + "bos_token_id": 151643, + "eos_token_id": 151643, + "max_new_tokens": 2048 +} + +[INFO|dynamic_module_utils.py:423] 2025-10-22 17:05:53,661 >> Could not locate the custom_generate/generate.py inside Qwen/Qwen2.5-0.5B. +[INFO|2025-10-22 17:05:53] llamafactory.model.model_utils.checkpointing:143 >> Gradient checkpointing enabled. +[INFO|2025-10-22 17:05:53] llamafactory.model.model_utils.attention:143 >> Using torch SDPA for faster training and inference. +[INFO|2025-10-22 17:05:53] llamafactory.model.adapter:143 >> Upcasting trainable params to float32. +[INFO|2025-10-22 17:05:53] llamafactory.model.adapter:143 >> Fine-tuning method: LoRA +[INFO|2025-10-22 17:05:53] llamafactory.model.model_utils.misc:143 >> Found linear modules: v_proj,q_proj,up_proj,gate_proj,o_proj,down_proj,k_proj +[INFO|2025-10-22 17:05:53] llamafactory.model.loader:143 >> trainable params: 4,399,104 || all params: 498,431,872 || trainable%: 0.8826 +[WARNING|trainer.py:906] 2025-10-22 17:05:53,775 >> The model is already on multiple devices. Skipping the move to device specified in `args`. +[INFO|trainer.py:699] 2025-10-22 17:05:53,777 >> max_steps is given, it will override any value given in num_train_epochs +[INFO|trainer.py:749] 2025-10-22 17:05:53,777 >> Using auto half precision backend +[WARNING|trainer.py:982] 2025-10-22 17:05:53,779 >> The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config werePAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None, 'pad_token_id': 151643}. +The model is already on multiple devices. Skipping the move to device specified in `args`. +The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None, 'pad_token_id': 151643}. +[INFO|trainer.py:2519] 2025-10-22 17:05:54,335 >> ***** Running training ***** +[INFO|trainer.py:2520] 2025-10-22 17:05:54,336 >> Num examples = 48,600 +[INFO|trainer.py:2521] 2025-10-22 17:05:54,336 >> Num Epochs = 1 +[INFO|trainer.py:2522] 2025-10-22 17:05:54,336 >> Instantaneous batch size per device = 1 +[INFO|trainer.py:2525] 2025-10-22 17:05:54,336 >> Total train batch size (w. parallel, distributed & accumulation) = 4 +[INFO|trainer.py:2526] 2025-10-22 17:05:54,336 >> Gradient Accumulation steps = 1 +[INFO|trainer.py:2527] 2025-10-22 17:05:54,336 >> Total optimization steps = 100 +[INFO|trainer.py:2528] 2025-10-22 17:05:54,337 >> Number of trainable parameters = 4,399,104 +[INFO|integration_utils.py:867] 2025-10-22 17:05:54,358 >> Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true" +wandb: Currently logged in as: zsprague (ut_nlp_deduce) to https://api.wandb.ai. Use `wandb login --relogin` to force relogin +wandb: Tracking run with wandb version 0.22.2 +wandb: Run data is saved locally in /scratch/zrs2020/LlamaFactoryHelper/wandb/run-20251022_170554-leoaij3x +wandb: Run `wandb offline` to turn off syncing. +wandb: Syncing run interactive_test +wandb: View project at https://wandb.ai/ut_nlp_deduce/llamafactory +wandb: View run at https://wandb.ai/ut_nlp_deduce/llamafactory/runs/leoaij3x + 0%| | 0/100 [00:00", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 940, in + main() + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 357, in wrapper + return f(*args, **kwargs) + ^^^^^^^^^^^^^^^^^^ + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 936, in main + run(args) + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 927, in run + elastic_launch( + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/launcher/api.py", line 156, in __call__ + return launch_agent(self._config, self._entrypoint, list(args)) + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/launcher/api.py", line 293, in launch_agent + raise ChildFailedError( +torch.distributed.elastic.multiprocessing.errors.ChildFailedError: +============================================================ +/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/train.py FAILED +------------------------------------------------------------ +Failures: +[1]: + time : 2025-10-22_17:07:47 + host : gl064.hpc.nyu.edu + rank : 1 (local_rank: 1) + exitcode : -15 (pid: 2396914) + error_file: + traceback : Signal 15 (SIGTERM) received by PID 2396914 +------------------------------------------------------------ +Root Cause (first observed failure): +[0]: + time : 2025-10-22_17:07:47 + host : gl064.hpc.nyu.edu + rank : 0 (local_rank: 0) + exitcode : -15 (pid: 2396913) + error_file: + traceback : Signal 15 (SIGTERM) received by PID 2396913 +============================================================ + +======================================== +ERROR: Training failed with exit code 1 +======================================== + +======================================== +Cleaning up LlamaFactory processes +======================================== +Cleaned up processes on gl064.hpc.nyu.edu +Cleaning up processes on worker node: gl065 +Process cleanup complete +======================================== +Job Name: lf_torch_test__interactive +Hostname: gl064.hpc.nyu.edu +Number of nodes: 2 +GPUs per node: 2 +Start Time: Wed Oct 22 05:10:12 PM EDT 2025 +Log file: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/logs/pipeline.log +======================================== +Sourcing secrets from: /scratch/zrs2020/LlamaFactoryHelper/secrets.env + +======================================== +Configuration Paths +======================================== +Train Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml +Merge Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/merge_config.yaml +Dataset Info: +Output Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints +Export Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged +HF Repo ID: TAUR-dev/testing_llamafactory_helper_quick_test__interactive + + +======================================== +STAGE 1: Training Model +Start Time: Wed Oct 22 05:10:15 PM EDT 2025 +======================================== + +Checking dataset cache status (master node only)... +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset 'TAUR-dev/D-SFT_C-BASELINE_r1_distillation-sft-data' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +============================================================ +Dataset Cache Preparation +============================================================ +Dataset: my_custom_sft8 +HF Hub URL: TAUR-dev/D-SFT_C-BASELINE_r1_distillation-sft-data +Attempting to load dataset (this triggers caching)... +Generating train split: 0%| | 0/3998 [00:00> Process rank: 3, world size: 4, device: cuda:1, distributed training: True, compute dtype: torch.float16 +[INFO|2025-10-22 17:10:47] llamafactory.hparams.parser:143 >> Set `ddp_find_unused_parameters` to False in DDP training since LoRA is enabled. +[INFO|2025-10-22 17:10:47] llamafactory.hparams.parser:423 >> Process rank: 2, world size: 4, device: cuda:0, distributed training: True, compute dtype: torch.float16 +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:47,575 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:47,575 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:47,575 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:47,575 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:47,575 >> loading file special_tokens_map.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:47,575 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:47,575 >> loading file chat_template.jinja from cache at None +[INFO|tokenization_utils_base.py:2364] 2025-10-22 17:10:47,748 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +[INFO|configuration_utils.py:765] 2025-10-22 17:10:47,945 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:839] 2025-10-22 17:10:47,947 >> Model config Qwen2Config { + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "dtype": "bfloat16", + "eos_token_id": 151643, + "hidden_act": "silu", + "hidden_size": 896, + "initializer_range": 0.02, + "intermediate_size": 4864, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 32768, + "max_window_layers": 24, + "model_type": "qwen2", + "num_attention_heads": 14, + "num_hidden_layers": 24, + "num_key_value_heads": 2, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 1000000.0, + "sliding_window": null, + "tie_word_embeddings": true, + "transformers_version": "4.57.1", + "use_cache": true, + "use_mrope": false, + "use_sliding_window": false, + "vocab_size": 151936 +} + +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:48,009 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:48,009 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:48,009 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:48,009 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:48,009 >> loading file special_tokens_map.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:48,009 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:10:48,009 >> loading file chat_template.jinja from cache at None +[INFO|tokenization_utils_base.py:2364] 2025-10-22 17:10:48,178 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +[INFO|2025-10-22 17:10:48] llamafactory.data.loader:143 >> Loading dataset TAUR-dev/D-SFT_C-BASELINE_r1_distillation-sft-data... +gl065:3801861:3801861 [1] NCCL INFO cudaDriverVersion 13000 +gl065:3801861:3801861 [1] NCCL INFO NCCL_SOCKET_IFNAME set by environment to ibs +gl065:3801861:3801861 [1] NCCL INFO Bootstrap: Using ibs3:10.0.5.1<0> +gl065:3801861:3801861 [1] NCCL INFO NCCL version 2.27.5+cuda12.9 +gl065:3801861:3801861 [1] NCCL INFO Comm config Blocking set to 1 +gl065:3801861:3801992 [1] NCCL INFO NET/Plugin: Could not find: libnccl-net.so. +gl065:3801861:3801992 [1] NCCL INFO NCCL_IB_DISABLE set by environment to 0. +gl065:3801861:3801992 [1] NCCL INFO NCCL_SOCKET_IFNAME set by environment to ibs +gl065:3801861:3801992 [1] NCCL INFO NCCL_IB_HCA set to mlx5 +gl065:3801861:3801992 [1] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [RO]; OOB ibs3:10.0.5.1<0> +gl065:3801861:3801992 [1] NCCL INFO Initialized NET plugin IB +gl065:3801861:3801992 [1] NCCL INFO Assigned NET 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Using internal tuner plugin. +gl065:3801860:3802002 [0] NCCL INFO ncclCommInitRankConfig comm 0x136f4ee0 rank 2 nranks 4 cudaDev 0 nvmlDev 0 busId 47000 commId 0x151fd45005ed7257 - Init COMPLETE +gl065:3801860:3802002 [0] NCCL INFO Init timings - ncclCommInitRankConfig: rank 2 nranks 4 total 0.13 (kernels 0.08, alloc 0.01, bootstrap 0.01, allgathers 0.00, topo 0.02, graphs 0.00, connections 0.00, rest 0.00) +gl065:3801860:3802010 [0] NCCL INFO Channel 00/0 : 1[1] -> 2[0] [receive] via NET/IB/0 +gl065:3801860:3802012 [0] NCCL INFO [Proxy Progress] Device 0 CPU core 14 +gl065:3801860:3802010 [0] NCCL INFO Channel 01/0 : 1[1] -> 2[0] [receive] via NET/IB/0 +gl065:3801860:3802010 [0] NCCL INFO Channel 00 : 2[0] -> 3[1] via SHM/direct/direct +gl065:3801860:3802010 [0] NCCL INFO Channel 01 : 2[0] -> 3[1] via SHM/direct/direct +gl065:3801861:3802011 [1] NCCL INFO Channel 00/0 : 3[1] -> 0[0] [send] via NET/IB/0 +gl065:3801861:3802011 [1] NCCL INFO Channel 01/0 : 3[1] -> 0[0] [send] via NET/IB/0 +gl065:3801861:3802013 [1] NCCL INFO [Proxy Progress] Device 1 CPU core 5 +gl065:3801860:3802010 [0] NCCL INFO Connected all rings, use ring PXN 0 GDR 0 +gl065:3801861:3802011 [1] NCCL INFO Connected all rings, use ring PXN 0 GDR 0 +Running tokenizer on dataset: 0%| | 0/3998 [00:00(your answer). + +# Problem +Using the numbers in the list [99, 57, 67], create an equation that equals 109. You can use basic arithmetic operations (+, -, *, /) and each number can only be used once. Your solution should include a series of steps "Step X:" where each step is a mathematical operation and the final step ultimately leads to the target number or it should be a single equation that results in the target. + +Give your answer in the following format: + +(your answer) + + +Where "(your answer)" is the list of steps to reach the target number or it should be a single equation that results in the target. + +For example: +If the list of numbers was [1, 2, 3] and the target was 1, you could write: + +Step 1: 1 + 2 = 3 +Step 2: 3 / 3 = 1 + + +or + + +(1 + 2) / 3 + + +Let's think step by step.<|endoftext|> +Assistant: +I have the numbers [99, 57, 67] and need to make 109 using basic arithmetic operations: addition, subtraction, multiplication, and division. Each number can only be used once. + +First, I should consider what operations might work. Since 109 is a bit larger than the numbers, multiplication might be involved, but 99 and 67 are both large, and 57 is smaller. Let me see the differences or sums. + +If I add 99 and 57, that's 99 + 57 = 156, which is bigger than 109. Then I have 67 left. If I subtract 67 from 156, that's 156 - 67 = 89, which is less than 109. 89 is too small. If I do 156 - 67 = 89, not 109. + +Maybe I can multiply. 99 times something. 99 * 1 = 99, too small. 99 * 2 = 198, too big. But I have to use the numbers given. + +Perhaps division. 99 divided by something. 99 / 1 = 99, not helpful. 99 / 0.9 or something, but I have to use the numbers. + +Another idea: maybe I can do 67 + 57 = 124, then 124 - 15, but I don't have 15, I have 99. 124 - 99 = 25, not 109. + +Not working. Let's list the numbers: 99, 57, 67. Target 109. + +Perhaps I need to use subtraction or division to get smaller numbers. + +Maybe (99 * something) + something. + +99 * 1 = 99, then I need +10, but I have 57 and 67, both larger than 10. + +67 - 57 = 10, then 99 + 10 = 109. Oh! That could work. + +So, first, 67 - 57 = 10, then 99 + 10 = 109. + +But in terms of steps, I need to use the numbers only once, and in this case, I used 67 and 57 to make 10, then added to 99. + +So, Step 1: 67 - 57 = 10 + +Step 2: 99 + 10 = 109 + +But 10 is not one of the original numbers; it's derived. But in the context, it should be fine, as per the example. + +In the example with [1,2,3] to make 1, they did (1+2)/3 or steps like 1+2=3 then 3/3=1. + +Similarly here, I can have steps. + +But let me confirm: using 67, 57, and 99. + +67 - 57 = 10, then 99 + 10 = 109. Yes. + +I could write it as an equation: 99 + (67 - 57) = 99 + 10 = 109. + +That seems correct. + +But is there another way? Maybe with multiplication or division. + +For example, 99 * 67 is huge, like 6633, divided by 57 or something. 6633 / 57. Let me calculate: 57 * 116 = 57*100=5700, 57*16=912, total 5700+912=6612, 6633-6612=21, so 116 + 21/57, not integer, and not 109. + +Not good. + +57 * 67 = ? 50*67=3350, 7*67=469, total 3350+469=3819, then divided by 99? 3819 / 99. 99*38=3762, 3819-3762=57, so 38 + 57/99, not 109. + +Not working. + +99 * 57 = 5643, divided by 67? 67*84=67*80=5360, 67*4=268, total 5360+268=5628, 5643-5628=15, so 84 + 15/67, not integer. + +Not 109. + +So, addition and subtraction seem better. + +Another combination: 99 + 67 = 166, then minus 57 = 166 - 57 = 109? 166 - 57. + +166 - 50 = 116, minus 7 more is 109? 116 - 7 = 109, yes! 166 - 57 = 109. + +166 - 57: 166 - 50 = 116, 116 - 7 = 109, yes. + +And 99 + 67 = 166, then 166 - 57 = 109. + +So, Step 1: 99 + 67 = 166 + +Step 2: 166 - 57 = 109 + +That also works. + +In this case, I used all three numbers directly. + +Similarly, in the first method, I used subtraction first. + +Both are valid. + +But in the first method, I had 67 - 57 first, then add to 99. + +Here, 99 + 67 first, then subtract 57. + +Now, which one to present? I think either is fine. + +But let me see the target: 109. + +In the second method, it's straightforward: (99 + 67) - 57 = 166 - 57 = 109. + +In the first: 99 + (67 - 57) = 99 + 10 = 109. + +Both are correct. + +Perhaps I should write it as a single equation. + +The problem says: "a series of steps" or "a single equation". + +I can do either. + +In the answer format, I can choose. + +But let me see if there's division or something, but not necessary. + +Another way: 109 is close to 100, but 99 is almost 100. + +99 + 10 = 109, and 10 from 67-57. + +Or directly. + +I think it's fine. + +Now, for the answer, I need to put it in the format. + +Also, in the steps, I need to specify the operations. + +In the first step-by-step: Step 1: 67 - 57 = 10, Step 2: 99 + 10 = 109. + +But in Step 2, I'm adding 99 and 10, but 10 is not a number, it's the result. But in the context, it should be acceptable, as per the example. + +Similarly, in the second: Step 1: 99 + 67 = 166, Step 2: 166 - 57 = 109. + +Here, 166 is intermediate. + +I could write the equation directly. + +Since the problem says "create an equation", but it allows steps or single equation. + +I think I'll go with the single equation for simplicity. + +So, (99 + 67) - 57 = 109 + +Or 99 + (67 - 57) = 109 + +Either way. + +Perhaps without parentheses, but order matters. + +99 + 67 - 57. + +Now, addition and subtraction have same precedence, left to right. + +So, 99 + 67 = 166, then 166 - 57 = 109, which is correct. + +Similarly, if I do 67 - 57 + 99, that's 10 + 99 = 109, also correct. + +So, in both cases, without parentheses, it works because of left to right evaluation. + +67 - 57 + 99: first 67 - 57 = 10, then 10 + 99 = 109. + +99 + 67 - 57: 99 + 67 = 166, 166 - 57 = 109. + +Both fine. + +So, I can write it as 99 + 67 - 57 = 109. + +Or 67 - 57 + 99 = 109. + +I think 99 + 67 - 57 is more natural. + +Since 99 is first in the list, but not necessary. + +In the list, it's [99, 57, 67], but order doesn't matter for the equation. + +In the steps, I might need to use them in order, but not specified. + +I think for the equation, it's fine. + +Now, to present. + +I think I'll write the single equation. + +But in the answer format, it should be enclosed in tags. + +Also, for the equation, I need to show it equals 109. + +Perhaps I can write: 99 + 67 - 57 = 109 + +But in the context, since it's the solution, it should be clear. + +Another thing: in the problem, it says "create an equation that equals 109", so I should have an expression equal to 109. + +So, (99 + 67) - 57 or something. + +But as I said, without parentheses it works. + +To be precise, I can use parentheses. + +But not necessary. + +I think it's fine. + +Perhaps I should write the steps to be consistent with the example. + +In the example, they had two options. + +I think I'll do both for clarity, but the problem says "give your answer" in the format, so one is enough. + +I'll go with the equation. + +So, 99 + 67 - 57 = 109 + +But in the equation, I need to use the numbers, and it should evaluate to 109. + +99 + 67 is 166, minus 57 is 109, yes. + +To write it as an expression: 99 + 67 - 57 + +But I need to show it equals 109. + +In the answer, I can write the equation. + +Similarly, in the step-by-step. + +I think either is fine. + +But let me see the problem: "your solution should include a series of steps... or it should be a single equation" + +I can choose. + +I think the single equation is concise. + +So, I'll do that. + +But in the list, 57 is second, but in the equation, I have 99 + 67 - 57, which uses all. + +Another combination: what if I use division? + +For example, 109 = 100 + 9, but not helpful. + +67 * 2 = 134, too big, minus 25, no. + +57 * 2 = 114, close to 109, 114 - 5, but no 5. + +114 - 5, but I have 99 and 67. + +114 - 5, but 5 not available. + +(57 * 2) - something, but I don't have 2, I have to use the numbers once, so I can't multiply by 2 unless I derive it. + +For example, I could do division to get fractions. + +Suppose I do 99 / 57 or something. + +99 / 57 = 33/19, approximately 1.736, not integer. + +Then multiply by 67? 1.736 * 67 116. something, not 109. + +Not good. + +67 / 57 1.175, times 99 116.325, not 109. + +No. + +So, addition and subtraction are the way to go. + +Therefore, 99 + 67 - 57 = 109 is correct. + +To write it with the numbers in order: but not necessary. + +I think I'm good. + +To solve the problem of creating an equation equal to 109 using the numbers [99, 57, 67] with basic arithmetic operations (+, -, *, /), each used once, I considered possible combinations. Since 109 is close to the sum of 99 and 67 (which is 166), subtracting 57 from this sum results in 166 - 57 = 109. This approach uses addition and subtraction, which are allowed operations. + +The equation can be written as: +\[ +99 + 67 - 57 = 109 +\] + +This is valid because: +- Addition and subtraction are performed left to right: first, \(99 + 67 = 166\), then \(166 - 57 = 109\). +- All numbers from the list are used exactly once. + +Alternatively, the equation can be expressed with parentheses for clarity, but they are not necessary due to left-to-right evaluation for operations of the same precedence: +\[ +(99 + 67) - 57 = 109 +\] + +Both forms yield the target number 109. + + +99 + 67 - 57 = 109 +<|endoftext|> + +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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Each number can only be used once. + +First, I should consider what operations might work. Since 109 is a bit larger than the numbers, multiplication might be involved, but 99 and 67 are both large, and 57 is smaller. Let me see the differences or sums. + +If I add 99 and 57, that's 99 + 57 = 156, which is bigger than 109. Then I have 67 left. If I subtract 67 from 156, that's 156 - 67 = 89, which is less than 109. 89 is too small. If I do 156 - 67 = 89, not 109. + +Maybe I can multiply. 99 times something. 99 * 1 = 99, too small. 99 * 2 = 198, too big. But I have to use the numbers given. + +Perhaps division. 99 divided by something. 99 / 1 = 99, not helpful. 99 / 0.9 or something, but I have to use the numbers. + +Another idea: maybe I can do 67 + 57 = 124, then 124 - 15, but I don't have 15, I have 99. 124 - 99 = 25, not 109. + +Not working. Let's list the numbers: 99, 57, 67. Target 109. + +Perhaps I need to use subtraction or division to get smaller numbers. + +Maybe (99 * something) + something. + +99 * 1 = 99, then I need +10, but I have 57 and 67, both larger than 10. + +67 - 57 = 10, then 99 + 10 = 109. Oh! That could work. + +So, first, 67 - 57 = 10, then 99 + 10 = 109. + +But in terms of steps, I need to use the numbers only once, and in this case, I used 67 and 57 to make 10, then added to 99. + +So, Step 1: 67 - 57 = 10 + +Step 2: 99 + 10 = 109 + +But 10 is not one of the original numbers; it's derived. But in the context, it should be fine, as per the example. + +In the example with [1,2,3] to make 1, they did (1+2)/3 or steps like 1+2=3 then 3/3=1. + +Similarly here, I can have steps. + +But let me confirm: using 67, 57, and 99. + +67 - 57 = 10, then 99 + 10 = 109. Yes. + +I could write it as an equation: 99 + (67 - 57) = 99 + 10 = 109. + +That seems correct. + +But is there another way? Maybe with multiplication or division. + +For example, 99 * 67 is huge, like 6633, divided by 57 or something. 6633 / 57. Let me calculate: 57 * 116 = 57*100=5700, 57*16=912, total 5700+912=6612, 6633-6612=21, so 116 + 21/57, not integer, and not 109. + +Not good. + +57 * 67 = ? 50*67=3350, 7*67=469, total 3350+469=3819, then divided by 99? 3819 / 99. 99*38=3762, 3819-3762=57, so 38 + 57/99, not 109. + +Not working. + +99 * 57 = 5643, divided by 67? 67*84=67*80=5360, 67*4=268, total 5360+268=5628, 5643-5628=15, so 84 + 15/67, not integer. + +Not 109. + +So, addition and subtraction seem better. + +Another combination: 99 + 67 = 166, then minus 57 = 166 - 57 = 109? 166 - 57. + +166 - 50 = 116, minus 7 more is 109? 116 - 7 = 109, yes! 166 - 57 = 109. + +166 - 57: 166 - 50 = 116, 116 - 7 = 109, yes. + +And 99 + 67 = 166, then 166 - 57 = 109. + +So, Step 1: 99 + 67 = 166 + +Step 2: 166 - 57 = 109 + +That also works. + +In this case, I used all three numbers directly. + +Similarly, in the first method, I used subtraction first. + +Both are valid. + +But in the first method, I had 67 - 57 first, then add to 99. + +Here, 99 + 67 first, then subtract 57. + +Now, which one to present? I think either is fine. + +But let me see the target: 109. + +In the second method, it's straightforward: (99 + 67) - 57 = 166 - 57 = 109. + +In the first: 99 + (67 - 57) = 99 + 10 = 109. + +Both are correct. + +Perhaps I should write it as a single equation. + +The problem says: "a series of steps" or "a single equation". + +I can do either. + +In the answer format, I can choose. + +But let me see if there's division or something, but not necessary. + +Another way: 109 is close to 100, but 99 is almost 100. + +99 + 10 = 109, and 10 from 67-57. + +Or directly. + +I think it's fine. + +Now, for the answer, I need to put it in the format. + +Also, in the steps, I need to specify the operations. + +In the first step-by-step: Step 1: 67 - 57 = 10, Step 2: 99 + 10 = 109. + +But in Step 2, I'm adding 99 and 10, but 10 is not a number, it's the result. But in the context, it should be acceptable, as per the example. + +Similarly, in the second: Step 1: 99 + 67 = 166, Step 2: 166 - 57 = 109. + +Here, 166 is intermediate. + +I could write the equation directly. + +Since the problem says "create an equation", but it allows steps or single equation. + +I think I'll go with the single equation for simplicity. + +So, (99 + 67) - 57 = 109 + +Or 99 + (67 - 57) = 109 + +Either way. + +Perhaps without parentheses, but order matters. + +99 + 67 - 57. + +Now, addition and subtraction have same precedence, left to right. + +So, 99 + 67 = 166, then 166 - 57 = 109, which is correct. + +Similarly, if I do 67 - 57 + 99, that's 10 + 99 = 109, also correct. + +So, in both cases, without parentheses, it works because of left to right evaluation. + +67 - 57 + 99: first 67 - 57 = 10, then 10 + 99 = 109. + +99 + 67 - 57: 99 + 67 = 166, 166 - 57 = 109. + +Both fine. + +So, I can write it as 99 + 67 - 57 = 109. + +Or 67 - 57 + 99 = 109. + +I think 99 + 67 - 57 is more natural. + +Since 99 is first in the list, but not necessary. + +In the list, it's [99, 57, 67], but order doesn't matter for the equation. + +In the steps, I might need to use them in order, but not specified. + +I think for the equation, it's fine. + +Now, to present. + +I think I'll write the single equation. + +But in the answer format, it should be enclosed in tags. + +Also, for the equation, I need to show it equals 109. + +Perhaps I can write: 99 + 67 - 57 = 109 + +But in the context, since it's the solution, it should be clear. + +Another thing: in the problem, it says "create an equation that equals 109", so I should have an expression equal to 109. + +So, (99 + 67) - 57 or something. + +But as I said, without parentheses it works. + +To be precise, I can use parentheses. + +But not necessary. + +I think it's fine. + +Perhaps I should write the steps to be consistent with the example. + +In the example, they had two options. + +I think I'll do both for clarity, but the problem says "give your answer" in the format, so one is enough. + +I'll go with the equation. + +So, 99 + 67 - 57 = 109 + +But in the equation, I need to use the numbers, and it should evaluate to 109. + +99 + 67 is 166, minus 57 is 109, yes. + +To write it as an expression: 99 + 67 - 57 + +But I need to show it equals 109. + +In the answer, I can write the equation. + +Similarly, in the step-by-step. + +I think either is fine. + +But let me see the problem: "your solution should include a series of steps... or it should be a single equation" + +I can choose. + +I think the single equation is concise. + +So, I'll do that. + +But in the list, 57 is second, but in the equation, I have 99 + 67 - 57, which uses all. + +Another combination: what if I use division? + +For example, 109 = 100 + 9, but not helpful. + +67 * 2 = 134, too big, minus 25, no. + +57 * 2 = 114, close to 109, 114 - 5, but no 5. + +114 - 5, but I have 99 and 67. + +114 - 5, but 5 not available. + +(57 * 2) - something, but I don't have 2, I have to use the numbers once, so I can't multiply by 2 unless I derive it. + +For example, I could do division to get fractions. + +Suppose I do 99 / 57 or something. + +99 / 57 = 33/19, approximately 1.736, not integer. + +Then multiply by 67? 1.736 * 67 116. something, not 109. + +Not good. + +67 / 57 1.175, times 99 116.325, not 109. + +No. + +So, addition and subtraction are the way to go. + +Therefore, 99 + 67 - 57 = 109 is correct. + +To write it with the numbers in order: but not necessary. + +I think I'm good. + +To solve the problem of creating an equation equal to 109 using the numbers [99, 57, 67] with basic arithmetic operations (+, -, *, /), each used once, I considered possible combinations. Since 109 is close to the sum of 99 and 67 (which is 166), subtracting 57 from this sum results in 166 - 57 = 109. This approach uses addition and subtraction, which are allowed operations. + +The equation can be written as: +\[ +99 + 67 - 57 = 109 +\] + +This is valid because: +- Addition and subtraction are performed left to right: first, \(99 + 67 = 166\), then \(166 - 57 = 109\). +- All numbers from the list are used exactly once. + +Alternatively, the equation can be expressed with parentheses for clarity, but they are not necessary due to left-to-right evaluation for operations of the same precedence: +\[ +(99 + 67) - 57 = 109 +\] + +Both forms yield the target number 109. + + +99 + 67 - 57 = 109 +<|endoftext|> + +gl065:3801861:3802007 [1] NCCL INFO [Service thread] Connection closed by localRank 0 +W1022 17:11:08.489000 3801814 site-packages/torch/distributed/elastic/multiprocessing/api.py:908] Sending process 3801861 closing signal SIGTERM +E1022 17:11:08.653000 3801814 site-packages/torch/distributed/elastic/multiprocessing/api.py:882] failed (exitcode: -7) local_rank: 0 (pid: 3801860) of binary: /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/bin/python +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 940, in + main() + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 357, in wrapper + return f(*args, **kwargs) + ^^^^^^^^^^^^^^^^^^ + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 936, in main + run(args) + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 927, in run + elastic_launch( + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/launcher/api.py", line 156, in __call__ + return launch_agent(self._config, self._entrypoint, list(args)) + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/launcher/api.py", line 293, in launch_agent + raise ChildFailedError( +torch.distributed.elastic.multiprocessing.errors.ChildFailedError: +============================================================ +/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/train.py FAILED +------------------------------------------------------------ +Failures: + +------------------------------------------------------------ +Root Cause (first observed failure): +[0]: + time : 2025-10-22_17:11:08 + host : gl065.hpc.nyu.edu + rank : 2 (local_rank: 0) + exitcode : -7 (pid: 3801860) + error_file: + traceback : Signal 7 (SIGBUS) received by PID 3801860 +============================================================ + +======================================== +ERROR: Training failed with exit code 1 +======================================== + +======================================== +Cleaning up LlamaFactory processes +======================================== +Cleaned up processes on gl065.hpc.nyu.edu +Process cleanup complete +======================================== +Job Name: lf_torch_test__interactive +Hostname: gl064.hpc.nyu.edu +Number of nodes: 2 +GPUs per node: 2 +Start Time: Wed Oct 22 05:14:39 PM EDT 2025 +Log file: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/logs/pipeline.log +======================================== +Sourcing secrets from: /scratch/zrs2020/LlamaFactoryHelper/secrets.env + +======================================== +Configuration Paths +======================================== +Train Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml +Merge Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/merge_config.yaml +Dataset Info: +Output Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints +Export Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged +HF Repo ID: TAUR-dev/testing_llamafactory_helper_quick_test__interactive + + +======================================== +STAGE 1: Training Model +Start Time: Wed Oct 22 05:14:42 PM EDT 2025 +======================================== + +Checking dataset cache status (master node only)... +Multi-node setup detected - skipping centralized preprocessing +Each node will process dataset independently with memory mapping disabled + +======================================== +Multi-Node Coordination +======================================== +This is the master node - launching worker nodes... +Master node: gl064 +Master port: 29500 +World size: 2 + +Launching on worker node 1: gl065 +All worker nodes launched successfully +Waiting 5 seconds for worker nodes to initialize... +======================================== +Job Name: lf_torch_test__interactive +Hostname: gl065.hpc.nyu.edu +Number of nodes: 2 +GPUs per node: 2 +Start Time: Wed Oct 22 05:14:44 PM EDT 2025 +Log file: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/logs/pipeline.log +======================================== +Sourcing secrets from: /scratch/zrs2020/LlamaFactoryHelper/secrets.env + +======================================== +Configuration Paths +======================================== +Train Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml +Merge Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/merge_config.yaml +Dataset Info: +Output Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints +Export Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged +HF Repo ID: TAUR-dev/testing_llamafactory_helper_quick_test__interactive + + +======================================== +STAGE 1: Training Model +Start Time: Wed Oct 22 05:14:46 PM EDT 2025 +======================================== +Worker node - skipping dataset preprocessing +Dataset memory mapping: DISABLED (worker node) +Worker node waiting for master to complete preprocessing... + +Proceeding with training... + +Multi-node training detected +Nodes: 2, GPUs per node: 2 +Master address: gl064 +Master port: 29500 +Node rank: 1 +World size: 2 +CUDA_VISIBLE_DEVICES: 0,1 +Using node-specific cache: /scratch/zrs2020/.cache/hf_cache/home/datasets_node1 +LLaMA-Factory path: /scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory +Training config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml + +Worker node: Adding extra 5 second delay for cache synchronization... +Starting distributed training with torch.distributed.run... + +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. + import pkg_resources +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. + import pkg_resources +[rank3]: Traceback (most recent call last): +[rank3]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/train.py", line 28, in +[rank3]: main() +[rank3]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/train.py", line 19, in main +[rank3]: run_exp() +[rank3]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/llamafactory/train/tuner.py", line 110, in run_exp +[rank3]: _training_function(config={"args": args, "callbacks": callbacks}) +[rank3]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/llamafactory/train/tuner.py", line 55, in _training_function +[rank3]: model_args, data_args, training_args, finetuning_args, generating_args = get_train_args(args) +[rank3]: ^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/llamafactory/hparams/parser.py", line 219, in get_train_args +[rank3]: model_args, data_args, training_args, finetuning_args, generating_args = _parse_train_args(args) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/llamafactory/hparams/parser.py", line 197, in _parse_train_args +[rank3]: return _parse_args(parser, args, allow_extra_keys=allow_extra_keys) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/llamafactory/hparams/parser.py", line 79, in _parse_args +[rank3]: return parser.parse_dict(args, allow_extra_keys=allow_extra_keys) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/hf_argparser.py", line 383, in parse_dict +[rank3]: raise ValueError(f"Some keys are not used by the HfArgumentParser: {sorted(unused_keys)}") +[rank3]: ValueError: Some keys are not used by the HfArgumentParser: ['keep_in_memory', 'load_from_cache_file'] +[rank2]: Traceback (most recent call last): +[rank2]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/train.py", line 28, in +[rank2]: main() +[rank2]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/train.py", line 19, in main +[rank2]: run_exp() +[rank2]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/llamafactory/train/tuner.py", line 110, in run_exp +[rank2]: _training_function(config={"args": args, "callbacks": callbacks}) +[rank2]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/llamafactory/train/tuner.py", line 55, in _training_function +[rank2]: model_args, data_args, training_args, finetuning_args, generating_args = get_train_args(args) +[rank2]: ^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/llamafactory/hparams/parser.py", line 219, in get_train_args +[rank2]: model_args, data_args, training_args, finetuning_args, generating_args = _parse_train_args(args) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/llamafactory/hparams/parser.py", line 197, in _parse_train_args +[rank2]: return _parse_args(parser, args, allow_extra_keys=allow_extra_keys) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/llamafactory/hparams/parser.py", line 79, in _parse_args +[rank2]: return parser.parse_dict(args, allow_extra_keys=allow_extra_keys) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/hf_argparser.py", line 383, in parse_dict +[rank2]: raise ValueError(f"Some keys are not used by the HfArgumentParser: {sorted(unused_keys)}") +[rank2]: ValueError: Some keys are not used by the HfArgumentParser: ['keep_in_memory', 'load_from_cache_file'] +[rank2]:[W1022 17:15:15.626379772 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) +E1022 17:15:16.684000 3805199 site-packages/torch/distributed/elastic/multiprocessing/api.py:882] failed (exitcode: 1) local_rank: 0 (pid: 3805246) of binary: /scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/bin/python +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 940, in + main() + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 357, in wrapper + return f(*args, **kwargs) + ^^^^^^^^^^^^^^^^^^ + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 936, in main + run(args) + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 927, in run + elastic_launch( + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/launcher/api.py", line 156, in __call__ + return launch_agent(self._config, self._entrypoint, list(args)) + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/launcher/api.py", line 293, in launch_agent + raise ChildFailedError( +torch.distributed.elastic.multiprocessing.errors.ChildFailedError: +============================================================ +/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/train.py FAILED +------------------------------------------------------------ +Failures: +[1]: + time : 2025-10-22_17:15:16 + host : gl065.hpc.nyu.edu + rank : 3 (local_rank: 1) + exitcode : 1 (pid: 3805247) + error_file: + traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html +------------------------------------------------------------ +Root Cause (first observed failure): +[0]: + time : 2025-10-22_17:15:16 + host : gl065.hpc.nyu.edu + rank : 2 (local_rank: 0) + exitcode : 1 (pid: 3805246) + error_file: + traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html +============================================================ +zen runpy>", line 88, in _run_code + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 940, in + main() + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 357, in wrapper + return f(*args, **kwargs) + ^^^^^^^^^^^^^^^^^^ + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 936, in main + run(args) + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/run.py", line 927, in run + elastic_launch( + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/launcher/api.py", line 156, in __call__ + return launch_agent(self._config, self._entrypoint, list(args)) + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/torch/distributed/launcher/api.py", line 293, in launch_agent + raise ChildFailedError( +torch.distributed.elastic.multiprocessing.errors.ChildFailedError: +============================================================ +/scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/src/train.py FAILED +------------------------------------------------------------ +Failures: + +------------------------------------------------------------ +Root Cause (first observed failure): +[0]: + time : 2025-10-22_17:15:16 + host : gl064.hpc.nyu.edu + rank : 1 (local_rank: 1) + exitcode : -15 (pid: 2398058) + error_file: + traceback : Signal 15 (SIGTERM) received by PID 2398058 +============================================================ +/scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/run_lf_torch_test__interactive.sh: line 506: syntax error near unexpected token `(' +/scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/run_lf_torch_test__interactive.sh: line 506: ` log "Skipping merge/export on worker node (rank $NODE_RANK)"' + +======================================== +Cleaning up LlamaFactory processes +======================================== +Process cleanup complete +Cleaned up processes on gl064.hpc.nyu.edu +Cleaning up processes on worker node: gl065 +Process cleanup complete +======================================== +Job Name: lf_torch_test__interactive +Hostname: gl064.hpc.nyu.edu +Number of nodes: 2 +GPUs per node: 2 +Start Time: Wed Oct 22 05:16:41 PM EDT 2025 +Log file: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/logs/pipeline.log +======================================== +Sourcing secrets from: /scratch/zrs2020/LlamaFactoryHelper/secrets.env + +======================================== +Configuration Paths +======================================== +Train Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml +Merge Config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/merge_config.yaml +Dataset Info: +Output Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints +Export Dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged +HF Repo ID: TAUR-dev/testing_llamafactory_helper_quick_test__interactive + + +======================================== +STAGE 1: Training Model +Start Time: Wed Oct 22 05:16:43 PM EDT 2025 +======================================== + +Checking dataset cache status (master node only)... +Multi-node setup detected - skipping centralized preprocessing +Each node will process dataset independently with memory mapping disabled + +======================================== +Multi-Node Coordination +======================================== +This is the master node - launching worker nodes... +Master node: gl064 +Master port: 29500 +World size: 2 + +Launching on worker node 1: gl065 +All worker nodes launched successfully +Waiting 5 seconds for worker nodes to initialize... +ed Oct 22 05:16:48 PM EDT 2025 +======================================== +Worker node - skipping dataset preprocessing +Dataset memory mapping: DISABLED (worker node) +Worker node waiting for master to complete preprocessing... +Master node (this node) will now join training as rank 0 + +Proceeding with training... + +Multi-node training detected +Nodes: 2, GPUs per node: 2 +Master address: gl064 +Master port: 29500 +Node rank: 0 +World size: 2 +CUDA_VISIBLE_DEVICES: 0,1 +Using node-specific cache: /scratch/zrs2020/.cache/hf_cache/home/datasets_node0 +LLaMA-Factory path: /scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory +Training config: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/train_config.yaml + +Starting distributed training with torch.distributed.run... + +***************************************** +Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +***************************************** +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. + import pkg_resources +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. + import pkg_resources +[INFO|2025-10-22 17:17:17] llamafactory.hparams.parser:143 >> Set `ddp_find_unused_parameters` to False in DDP training since LoRA is enabled. +[INFO|2025-10-22 17:17:17] llamafactory.hparams.parser:423 >> Process rank: 0, world size: 4, device: cuda:0, distributed training: True, compute dtype: torch.float16 +[INFO|2025-10-22 17:17:17] llamafactory.hparams.parser:423 >> Process rank: 1, world size: 4, device: cuda:1, distributed training: True, compute dtype: torch.float16 +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,193 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,193 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,193 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,193 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,193 >> loading file special_tokens_map.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,193 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,193 >> loading file chat_template.jinja from cache at None +[INFO|tokenization_utils_base.py:2364] 2025-10-22 17:17:17,364 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +[INFO|configuration_utils.py:765] 2025-10-22 17:17:17,575 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:839] 2025-10-22 17:17:17,577 >> Model config Qwen2Config { + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "dtype": "bfloat16", + "eos_token_id": 151643, + "hidden_act": "silu", + "hidden_size": 896, + "initializer_range": 0.02, + "intermediate_size": 4864, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 32768, + "max_window_layers": 24, + "model_type": "qwen2", + "num_attention_heads": 14, + "num_hidden_layers": 24, + "num_key_value_heads": 2, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 1000000.0, + "sliding_window": null, + "tie_word_embeddings": true, + "transformers_version": "4.57.1", + "use_cache": true, + "use_mrope": false, + "use_sliding_window": false, + "vocab_size": 151936 +} + +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,650 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,650 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,650 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,650 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,650 >> loading file special_tokens_map.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,650 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:17:17,650 >> loading file chat_template.jinja from cache at None +[INFO|tokenization_utils_base.py:2364] 2025-10-22 17:17:17,816 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +[INFO|2025-10-22 17:17:17] llamafactory.data.loader:143 >> Loading dataset TAUR-dev/D-SFT_C-BASELINE_r1_distillation-sft-data... +Generating train split: 0%| | 0/3998 [00:00 +gl064:2405035:2405035 [0] NCCL INFO cudaDriverVersion 13000 +gl064:2405035:2405035 [0] NCCL INFO NCCL version 2.27.5+cuda12.9 +gl064:2405035:2405035 [0] NCCL INFO Comm config Blocking set to 1 +gl064:2405036:2405036 [1] NCCL INFO cudaDriverVersion 13000 +gl064:2405036:2405036 [1] NCCL INFO NCCL_SOCKET_IFNAME set by environment to ibs +gl064:2405036:2405036 [1] NCCL INFO Bootstrap: Using ibs3:10.0.5.0<0> +gl064:2405036:2405036 [1] NCCL INFO NCCL version 2.27.5+cuda12.9 +gl064:2405036:2405036 [1] NCCL INFO Comm config Blocking set to 1 +gl064:2405035:2405115 [0] NCCL 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Using internal tuner plugin. +gl064:2405035:2405115 [0] NCCL INFO ncclCommInitRankConfig comm 0x1566a120 rank 0 nranks 4 cudaDev 0 nvmlDev 0 busId 47000 commId 0xc2d14dfa6fbc170b - Init COMPLETE +gl064:2405035:2405115 [0] NCCL INFO Init timings - ncclCommInitRankConfig: rank 0 nranks 4 total 0.45 (kernels 0.09, alloc 0.01, bootstrap 0.32, allgathers 0.02, topo 0.01, graphs 0.00, connections 0.00, rest 0.00) +gl064:2405035:2405125 [0] NCCL INFO Channel 00/0 : 3[1] -> 0[0] [receive] via NET/IB/0 +gl064:2405035:2405127 [0] NCCL INFO [Proxy Progress] Device 0 CPU core 17 +gl064:2405035:2405125 [0] NCCL INFO Channel 01/0 : 3[1] -> 0[0] [receive] via NET/IB/0 +gl064:2405035:2405125 [0] NCCL INFO Channel 00 : 0[0] -> 1[1] via SHM/direct/direct +gl064:2405035:2405125 [0] NCCL INFO Channel 01 : 0[0] -> 1[1] via SHM/direct/direct +gl064:2405036:2405126 [1] NCCL INFO Channel 00/0 : 1[1] -> 2[0] [send] via NET/IB/0 +gl064:2405036:2405126 [1] NCCL INFO Channel 01/0 : 1[1] -> 2[0] [send] via NET/IB/0 +gl064:2405036:2405128 [1] NCCL INFO [Proxy Progress] Device 1 CPU core 19 +gl064:2405035:2405125 [0] NCCL INFO Connected all rings, use ring PXN 0 GDR 0 +gl064:2405036:2405126 [1] NCCL INFO Connected all rings, use ring PXN 0 GDR 0 +Running tokenizer on dataset: 0%| | 0/3998 [00:00(your answer). + +# Problem +Using the numbers in the list [99, 57, 67], create an equation that equals 109. You can use basic arithmetic operations (+, -, *, /) and each number can only be used once. Your solution should include a series of steps "Step X:" where each step is a mathematical operation and the final step ultimately leads to the target number or it should be a single equation that results in the target. + +Give your answer in the following format: + +(your answer) + + +Where "(your answer)" is the list of steps to reach the target number or it should be a single equation that results in the target. + +For example: +If the list of numbers was [1, 2, 3] and the target was 1, you could write: + +Step 1: 1 + 2 = 3 +Step 2: 3 / 3 = 1 + + +or + + +(1 + 2) / 3 + + +Let's think step by step.<|endoftext|> +Assistant: +I have the numbers [99, 57, 67] and need to make 109 using basic arithmetic operations: addition, subtraction, multiplication, and division. Each number can only be used once. + +First, I should consider what operations might work. Since 109 is a bit larger than the numbers, multiplication might be involved, but 99 and 67 are both large, and 57 is smaller. Let me see the differences or sums. + +If I add 99 and 57, that's 99 + 57 = 156, which is bigger than 109. Then I have 67 left. If I subtract 67 from 156, that's 156 - 67 = 89, which is less than 109. 89 is too small. If I do 156 - 67 = 89, not 109. + +Maybe I can multiply. 99 times something. 99 * 1 = 99, too small. 99 * 2 = 198, too big. But I have to use the numbers given. + +Perhaps division. 99 divided by something. 99 / 1 = 99, not helpful. 99 / 0.9 or something, but I have to use the numbers. + +Another idea: maybe I can do 67 + 57 = 124, then 124 - 15, but I don't have 15, I have 99. 124 - 99 = 25, not 109. + +Not working. Let's list the numbers: 99, 57, 67. Target 109. + +Perhaps I need to use subtraction or division to get smaller numbers. + +Maybe (99 * something) + something. + +99 * 1 = 99, then I need +10, but I have 57 and 67, both larger than 10. + +67 - 57 = 10, then 99 + 10 = 109. Oh! That could work. + +So, first, 67 - 57 = 10, then 99 + 10 = 109. + +But in terms of steps, I need to use the numbers only once, and in this case, I used 67 and 57 to make 10, then added to 99. + +So, Step 1: 67 - 57 = 10 + +Step 2: 99 + 10 = 109 + +But 10 is not one of the original numbers; it's derived. But in the context, it should be fine, as per the example. + +In the example with [1,2,3] to make 1, they did (1+2)/3 or steps like 1+2=3 then 3/3=1. + +Similarly here, I can have steps. + +But let me confirm: using 67, 57, and 99. + +67 - 57 = 10, then 99 + 10 = 109. Yes. + +I could write it as an equation: 99 + (67 - 57) = 99 + 10 = 109. + +That seems correct. + +But is there another way? Maybe with multiplication or division. + +For example, 99 * 67 is huge, like 6633, divided by 57 or something. 6633 / 57. Let me calculate: 57 * 116 = 57*100=5700, 57*16=912, total 5700+912=6612, 6633-6612=21, so 116 + 21/57, not integer, and not 109. + +Not good. + +57 * 67 = ? 50*67=3350, 7*67=469, total 3350+469=3819, then divided by 99? 3819 / 99. 99*38=3762, 3819-3762=57, so 38 + 57/99, not 109. + +Not working. + +99 * 57 = 5643, divided by 67? 67*84=67*80=5360, 67*4=268, total 5360+268=5628, 5643-5628=15, so 84 + 15/67, not integer. + +Not 109. + +So, addition and subtraction seem better. + +Another combination: 99 + 67 = 166, then minus 57 = 166 - 57 = 109? 166 - 57. + +166 - 50 = 116, minus 7 more is 109? 116 - 7 = 109, yes! 166 - 57 = 109. + +166 - 57: 166 - 50 = 116, 116 - 7 = 109, yes. + +And 99 + 67 = 166, then 166 - 57 = 109. + +So, Step 1: 99 + 67 = 166 + +Step 2: 166 - 57 = 109 + +That also works. + +In this case, I used all three numbers directly. + +Similarly, in the first method, I used subtraction first. + +Both are valid. + +But in the first method, I had 67 - 57 first, then add to 99. + +Here, 99 + 67 first, then subtract 57. + +Now, which one to present? I think either is fine. + +But let me see the target: 109. + +In the second method, it's straightforward: (99 + 67) - 57 = 166 - 57 = 109. + +In the first: 99 + (67 - 57) = 99 + 10 = 109. + +Both are correct. + +Perhaps I should write it as a single equation. + +The problem says: "a series of steps" or "a single equation". + +I can do either. + +In the answer format, I can choose. + +But let me see if there's division or something, but not necessary. + +Another way: 109 is close to 100, but 99 is almost 100. + +99 + 10 = 109, and 10 from 67-57. + +Or directly. + +I think it's fine. + +Now, for the answer, I need to put it in the format. + +Also, in the steps, I need to specify the operations. + +In the first step-by-step: Step 1: 67 - 57 = 10, Step 2: 99 + 10 = 109. + +But in Step 2, I'm adding 99 and 10, but 10 is not a number, it's the result. But in the context, it should be acceptable, as per the example. + +Similarly, in the second: Step 1: 99 + 67 = 166, Step 2: 166 - 57 = 109. + +Here, 166 is intermediate. + +I could write the equation directly. + +Since the problem says "create an equation", but it allows steps or single equation. + +I think I'll go with the single equation for simplicity. + +So, (99 + 67) - 57 = 109 + +Or 99 + (67 - 57) = 109 + +Either way. + +Perhaps without parentheses, but order matters. + +99 + 67 - 57. + +Now, addition and subtraction have same precedence, left to right. + +So, 99 + 67 = 166, then 166 - 57 = 109, which is correct. + +Similarly, if I do 67 - 57 + 99, that's 10 + 99 = 109, also correct. + +So, in both cases, without parentheses, it works because of left to right evaluation. + +67 - 57 + 99: first 67 - 57 = 10, then 10 + 99 = 109. + +99 + 67 - 57: 99 + 67 = 166, 166 - 57 = 109. + +Both fine. + +So, I can write it as 99 + 67 - 57 = 109. + +Or 67 - 57 + 99 = 109. + +I think 99 + 67 - 57 is more natural. + +Since 99 is first in the list, but not necessary. + +In the list, it's [99, 57, 67], but order doesn't matter for the equation. + +In the steps, I might need to use them in order, but not specified. + +I think for the equation, it's fine. + +Now, to present. + +I think I'll write the single equation. + +But in the answer format, it should be enclosed in tags. + +Also, for the equation, I need to show it equals 109. + +Perhaps I can write: 99 + 67 - 57 = 109 + +But in the context, since it's the solution, it should be clear. + +Another thing: in the problem, it says "create an equation that equals 109", so I should have an expression equal to 109. + +So, (99 + 67) - 57 or something. + +But as I said, without parentheses it works. + +To be precise, I can use parentheses. + +But not necessary. + +I think it's fine. + +Perhaps I should write the steps to be consistent with the example. + +In the example, they had two options. + +I think I'll do both for clarity, but the problem says "give your answer" in the format, so one is enough. + +I'll go with the equation. + +So, 99 + 67 - 57 = 109 + +But in the equation, I need to use the numbers, and it should evaluate to 109. + +99 + 67 is 166, minus 57 is 109, yes. + +To write it as an expression: 99 + 67 - 57 + +But I need to show it equals 109. + +In the answer, I can write the equation. + +Similarly, in the step-by-step. + +I think either is fine. + +But let me see the problem: "your solution should include a series of steps... or it should be a single equation" + +I can choose. + +I think the single equation is concise. + +So, I'll do that. + +But in the list, 57 is second, but in the equation, I have 99 + 67 - 57, which uses all. + +Another combination: what if I use division? + +For example, 109 = 100 + 9, but not helpful. + +67 * 2 = 134, too big, minus 25, no. + +57 * 2 = 114, close to 109, 114 - 5, but no 5. + +114 - 5, but I have 99 and 67. + +114 - 5, but 5 not available. + +(57 * 2) - something, but I don't have 2, I have to use the numbers once, so I can't multiply by 2 unless I derive it. + +For example, I could do division to get fractions. + +Suppose I do 99 / 57 or something. + +99 / 57 = 33/19, approximately 1.736, not integer. + +Then multiply by 67? 1.736 * 67 116. something, not 109. + +Not good. + +67 / 57 1.175, times 99 116.325, not 109. + +No. + +So, addition and subtraction are the way to go. + +Therefore, 99 + 67 - 57 = 109 is correct. + +To write it with the numbers in order: but not necessary. + +I think I'm good. + +To solve the problem of creating an equation equal to 109 using the numbers [99, 57, 67] with basic arithmetic operations (+, -, *, /), each used once, I considered possible combinations. Since 109 is close to the sum of 99 and 67 (which is 166), subtracting 57 from this sum results in 166 - 57 = 109. This approach uses addition and subtraction, which are allowed operations. + +The equation can be written as: +\[ +99 + 67 - 57 = 109 +\] + +This is valid because: +- Addition and subtraction are performed left to right: first, \(99 + 67 = 166\), then \(166 - 57 = 109\). +- All numbers from the list are used exactly once. + +Alternatively, the equation can be expressed with parentheses for clarity, but they are not necessary due to left-to-right evaluation for operations of the same precedence: +\[ +(99 + 67) - 57 = 109 +\] + +Both forms yield the target number 109. + + +99 + 67 - 57 = 109 +<|endoftext|> + +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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Each number can only be used once. + +First, I should consider what operations might work. Since 109 is a bit larger than the numbers, multiplication might be involved, but 99 and 67 are both large, and 57 is smaller. Let me see the differences or sums. + +If I add 99 and 57, that's 99 + 57 = 156, which is bigger than 109. Then I have 67 left. If I subtract 67 from 156, that's 156 - 67 = 89, which is less than 109. 89 is too small. If I do 156 - 67 = 89, not 109. + +Maybe I can multiply. 99 times something. 99 * 1 = 99, too small. 99 * 2 = 198, too big. But I have to use the numbers given. + +Perhaps division. 99 divided by something. 99 / 1 = 99, not helpful. 99 / 0.9 or something, but I have to use the numbers. + +Another idea: maybe I can do 67 + 57 = 124, then 124 - 15, but I don't have 15, I have 99. 124 - 99 = 25, not 109. + +Not working. Let's list the numbers: 99, 57, 67. Target 109. + +Perhaps I need to use subtraction or division to get smaller numbers. + +Maybe (99 * something) + something. + +99 * 1 = 99, then I need +10, but I have 57 and 67, both larger than 10. + +67 - 57 = 10, then 99 + 10 = 109. Oh! That could work. + +So, first, 67 - 57 = 10, then 99 + 10 = 109. + +But in terms of steps, I need to use the numbers only once, and in this case, I used 67 and 57 to make 10, then added to 99. + +So, Step 1: 67 - 57 = 10 + +Step 2: 99 + 10 = 109 + +But 10 is not one of the original numbers; it's derived. But in the context, it should be fine, as per the example. + +In the example with [1,2,3] to make 1, they did (1+2)/3 or steps like 1+2=3 then 3/3=1. + +Similarly here, I can have steps. + +But let me confirm: using 67, 57, and 99. + +67 - 57 = 10, then 99 + 10 = 109. Yes. + +I could write it as an equation: 99 + (67 - 57) = 99 + 10 = 109. + +That seems correct. + +But is there another way? Maybe with multiplication or division. + +For example, 99 * 67 is huge, like 6633, divided by 57 or something. 6633 / 57. Let me calculate: 57 * 116 = 57*100=5700, 57*16=912, total 5700+912=6612, 6633-6612=21, so 116 + 21/57, not integer, and not 109. + +Not good. + +57 * 67 = ? 50*67=3350, 7*67=469, total 3350+469=3819, then divided by 99? 3819 / 99. 99*38=3762, 3819-3762=57, so 38 + 57/99, not 109. + +Not working. + +99 * 57 = 5643, divided by 67? 67*84=67*80=5360, 67*4=268, total 5360+268=5628, 5643-5628=15, so 84 + 15/67, not integer. + +Not 109. + +So, addition and subtraction seem better. + +Another combination: 99 + 67 = 166, then minus 57 = 166 - 57 = 109? 166 - 57. + +166 - 50 = 116, minus 7 more is 109? 116 - 7 = 109, yes! 166 - 57 = 109. + +166 - 57: 166 - 50 = 116, 116 - 7 = 109, yes. + +And 99 + 67 = 166, then 166 - 57 = 109. + +So, Step 1: 99 + 67 = 166 + +Step 2: 166 - 57 = 109 + +That also works. + +In this case, I used all three numbers directly. + +Similarly, in the first method, I used subtraction first. + +Both are valid. + +But in the first method, I had 67 - 57 first, then add to 99. + +Here, 99 + 67 first, then subtract 57. + +Now, which one to present? I think either is fine. + +But let me see the target: 109. + +In the second method, it's straightforward: (99 + 67) - 57 = 166 - 57 = 109. + +In the first: 99 + (67 - 57) = 99 + 10 = 109. + +Both are correct. + +Perhaps I should write it as a single equation. + +The problem says: "a series of steps" or "a single equation". + +I can do either. + +In the answer format, I can choose. + +But let me see if there's division or something, but not necessary. + +Another way: 109 is close to 100, but 99 is almost 100. + +99 + 10 = 109, and 10 from 67-57. + +Or directly. + +I think it's fine. + +Now, for the answer, I need to put it in the format. + +Also, in the steps, I need to specify the operations. + +In the first step-by-step: Step 1: 67 - 57 = 10, Step 2: 99 + 10 = 109. + +But in Step 2, I'm adding 99 and 10, but 10 is not a number, it's the result. But in the context, it should be acceptable, as per the example. + +Similarly, in the second: Step 1: 99 + 67 = 166, Step 2: 166 - 57 = 109. + +Here, 166 is intermediate. + +I could write the equation directly. + +Since the problem says "create an equation", but it allows steps or single equation. + +I think I'll go with the single equation for simplicity. + +So, (99 + 67) - 57 = 109 + +Or 99 + (67 - 57) = 109 + +Either way. + +Perhaps without parentheses, but order matters. + +99 + 67 - 57. + +Now, addition and subtraction have same precedence, left to right. + +So, 99 + 67 = 166, then 166 - 57 = 109, which is correct. + +Similarly, if I do 67 - 57 + 99, that's 10 + 99 = 109, also correct. + +So, in both cases, without parentheses, it works because of left to right evaluation. + +67 - 57 + 99: first 67 - 57 = 10, then 10 + 99 = 109. + +99 + 67 - 57: 99 + 67 = 166, 166 - 57 = 109. + +Both fine. + +So, I can write it as 99 + 67 - 57 = 109. + +Or 67 - 57 + 99 = 109. + +I think 99 + 67 - 57 is more natural. + +Since 99 is first in the list, but not necessary. + +In the list, it's [99, 57, 67], but order doesn't matter for the equation. + +In the steps, I might need to use them in order, but not specified. + +I think for the equation, it's fine. + +Now, to present. + +I think I'll write the single equation. + +But in the answer format, it should be enclosed in tags. + +Also, for the equation, I need to show it equals 109. + +Perhaps I can write: 99 + 67 - 57 = 109 + +But in the context, since it's the solution, it should be clear. + +Another thing: in the problem, it says "create an equation that equals 109", so I should have an expression equal to 109. + +So, (99 + 67) - 57 or something. + +But as I said, without parentheses it works. + +To be precise, I can use parentheses. + +But not necessary. + +I think it's fine. + +Perhaps I should write the steps to be consistent with the example. + +In the example, they had two options. + +I think I'll do both for clarity, but the problem says "give your answer" in the format, so one is enough. + +I'll go with the equation. + +So, 99 + 67 - 57 = 109 + +But in the equation, I need to use the numbers, and it should evaluate to 109. + +99 + 67 is 166, minus 57 is 109, yes. + +To write it as an expression: 99 + 67 - 57 + +But I need to show it equals 109. + +In the answer, I can write the equation. + +Similarly, in the step-by-step. + +I think either is fine. + +But let me see the problem: "your solution should include a series of steps... or it should be a single equation" + +I can choose. + +I think the single equation is concise. + +So, I'll do that. + +But in the list, 57 is second, but in the equation, I have 99 + 67 - 57, which uses all. + +Another combination: what if I use division? + +For example, 109 = 100 + 9, but not helpful. + +67 * 2 = 134, too big, minus 25, no. + +57 * 2 = 114, close to 109, 114 - 5, but no 5. + +114 - 5, but I have 99 and 67. + +114 - 5, but 5 not available. + +(57 * 2) - something, but I don't have 2, I have to use the numbers once, so I can't multiply by 2 unless I derive it. + +For example, I could do division to get fractions. + +Suppose I do 99 / 57 or something. + +99 / 57 = 33/19, approximately 1.736, not integer. + +Then multiply by 67? 1.736 * 67 116. something, not 109. + +Not good. + +67 / 57 1.175, times 99 116.325, not 109. + +No. + +So, addition and subtraction are the way to go. + +Therefore, 99 + 67 - 57 = 109 is correct. + +To write it with the numbers in order: but not necessary. + +I think I'm good. + +To solve the problem of creating an equation equal to 109 using the numbers [99, 57, 67] with basic arithmetic operations (+, -, *, /), each used once, I considered possible combinations. Since 109 is close to the sum of 99 and 67 (which is 166), subtracting 57 from this sum results in 166 - 57 = 109. This approach uses addition and subtraction, which are allowed operations. + +The equation can be written as: +\[ +99 + 67 - 57 = 109 +\] + +This is valid because: +- Addition and subtraction are performed left to right: first, \(99 + 67 = 166\), then \(166 - 57 = 109\). +- All numbers from the list are used exactly once. + +Alternatively, the equation can be expressed with parentheses for clarity, but they are not necessary due to left-to-right evaluation for operations of the same precedence: +\[ +(99 + 67) - 57 = 109 +\] + +Both forms yield the target number 109. + + +99 + 67 - 57 = 109 +<|endoftext|> + +[INFO|configuration_utils.py:765] 2025-10-22 17:17:36,697 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:839] 2025-10-22 17:17:36,697 >> Model config Qwen2Config { + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "dtype": "bfloat16", + "eos_token_id": 151643, + "hidden_act": "silu", + "hidden_size": 896, + "initializer_range": 0.02, + "intermediate_size": 4864, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 32768, + "max_window_layers": 24, + "model_type": "qwen2", + "num_attention_heads": 14, + "num_hidden_layers": 24, + "num_key_value_heads": 2, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 1000000.0, + "sliding_window": null, + "tie_word_embeddings": true, + "transformers_version": "4.57.1", + "use_cache": true, + "use_mrope": false, + "use_sliding_window": false, + "vocab_size": 151936 +} + +[INFO|2025-10-22 17:17:36] llamafactory.model.model_utils.kv_cache:143 >> KV cache is disabled during training. +[WARNING|logging.py:328] 2025-10-22 17:17:37,279 >> `torch_dtype` is deprecated! Use `dtype` instead! +`torch_dtype` is deprecated! Use `dtype` instead! +[INFO|modeling_utils.py:1172] 2025-10-22 17:17:37,281 >> loading weights file model.safetensors from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/model.safetensors +[INFO|modeling_utils.py:2341] 2025-10-22 17:17:37,282 >> Instantiating Qwen2ForCausalLM model under default dtype torch.float16. +[INFO|configuration_utils.py:986] 2025-10-22 17:17:37,283 >> Generate config GenerationConfig { + "bos_token_id": 151643, + "eos_token_id": 151643, + "use_cache": false +} + +[INFO|configuration_utils.py:941] 2025-10-22 17:17:37,726 >> loading configuration file generation_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/generation_config.json +[INFO|configuration_utils.py:986] 2025-10-22 17:17:37,726 >> Generate config GenerationConfig { + "bos_token_id": 151643, + "eos_token_id": 151643, + "max_new_tokens": 2048 +} + +[INFO|dynamic_module_utils.py:423] 2025-10-22 17:17:37,765 >> Could not locate the custom_generate/generate.py inside Qwen/Qwen2.5-0.5B. +[INFO|2025-10-22 17:17:37] llamafactory.model.model_utils.checkpointing:143 >> Gradient checkpointing enabled. +[INFO|2025-10-22 17:17:37] llamafactory.model.model_utils.attention:143 >> Using torch SDPA for faster training and inference. +[INFO|2025-10-22 17:17:37] llamafactory.model.adapter:143 >> Upcasting trainable params to float32. +[INFO|2025-10-22 17:17:37] llamafactory.model.adapter:143 >> Fine-tuning method: LoRA +[INFO|2025-10-22 17:17:37] llamafactory.model.model_utils.misc:143 >> Found linear modules: q_proj,down_proj,k_proj,o_proj,v_proj,up_proj,gate_proj +[INFO|2025-10-22 17:17:37] llamafactory.model.loader:143 >> trainable params: 4,399,104 || all params: 498,431,872 || trainable%: 0.8826 +[WARNING|trainer.py:906] 2025-10-22 17:17:37,873 >> The model is already on multiple devices. Skipping the move to device specified in `args`. +The model is already on multiple devices. Skipping the move to device specified in `args`. +[INFO|trainer.py:699] 2025-10-22 17:17:37,875 >> max_steps is given, it will override any value given in num_train_epochs +[INFO|trainer.py:749] 2025-10-22 17:17:37,875 >> Using auto half precision backend +[WARNING|trainer.py:982] 2025-10-22 17:17:37,877 >> The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None, 'pad_token_id': 151643}. +The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None, 'pad_token_id': 151643}. +[INFO|trainer.py:2519] 2025-10-22 17:17:38,056 >> ***** Running training ***** +[INFO|trainer.py:2520] 2025-10-22 17:17:38,056 >> Num examples = 3,598 +[INFO|trainer.py:2521] 2025-10-22 17:17:38,056 >> Num Epochs = 1 +[INFO|trainer.py:2522] 2025-10-22 17:17:38,056 >> Instantaneous batch size per device = 1 +[INFO|trainer.py:2525] 2025-10-22 17:17:38,056 >> Total train batch size (w. parallel, distributed & accumulation) = 4 +[INFO|trainer.py:2526] 2025-10-22 17:17:38,056 >> Gradient Accumulation steps = 1 +[INFO|trainer.py:2527] 2025-10-22 17:17:38,056 >> Total optimization steps = 100 +[INFO|trainer.py:2528] 2025-10-22 17:17:38,058 >> Number of trainable parameters = 4,399,104 +[INFO|integration_utils.py:867] 2025-10-22 17:17:38,078 >> Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true" +wandb: Currently logged in as: zsprague (ut_nlp_deduce) to https://api.wandb.ai. Use `wandb login --relogin` to force relogin +wandb: Tracking run with wandb version 0.22.2 +wandb: Run data is saved locally in /scratch/zrs2020/LlamaFactoryHelper/wandb/run-20251022_171738-yru7qzfl +wandb: Run `wandb offline` to turn off syncing. +wandb: Syncing run interactive_test +wandb: View project at https://wandb.ai/ut_nlp_deduce/llamafactory +wandb: View run at https://wandb.ai/ut_nlp_deduce/llamafactory/runs/yru7qzfl + 0%| | 0/100 [00:00> Saving model checkpoint to /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-50 +[INFO|configuration_utils.py:765] 2025-10-22 17:17:57,898 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:839] 2025-10-22 17:17:57,899 >> Model config Qwen2Config { + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "dtype": "bfloat16", + "eos_token_id": 151643, + "hidden_act": "silu", + "hidden_size": 896, + "initializer_range": 0.02, + "intermediate_size": 4864, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 32768, + "max_window_layers": 24, + "model_type": "qwen2", + "num_attention_heads": 14, + "num_hidden_layers": 24, + "num_key_value_heads": 2, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 1000000.0, + "sliding_window": null, + "tie_word_embeddings": true, + "transformers_version": "4.57.1", + "use_cache": true, + "use_mrope": false, + "use_sliding_window": false, + "vocab_size": 151936 +} + +[INFO|tokenization_utils_base.py:2421] 2025-10-22 17:17:58,060 >> chat template saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-50/chat_template.jinja +[INFO|tokenization_utils_base.py:2590] 2025-10-22 17:17:58,065 >> tokenizer config file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-50/tokenizer_config.json +[INFO|tokenization_utils_base.py:2599] 2025-10-22 17:17:58,087 >> Special tokens file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-50/special_tokens_map.json + 51%| | 51/100 [00:19<00:28, 1.72it/s] 52%| | 52/100 [00:20<00:24, 1.97it/s] 53%| | 53/100 [00:20<00:22, 2.06it/s] 54%| | 54/100 [00:21<00:23, 1.96it/s] 55%| | 55/100 [00:21<00:20, 2.16it/s] 56%| | 56/100 [00:21<00:18, 2.41it/s] 57%| | 57/100 [00:22<00:20, 2.08it/s] 58%| | 58/100 [00:22<00:18, 2.27it/s] 59%| | 59/100 [00:23<00:16, 2.49it/s] 60%| | 60/100 [00:23<00:14, 2.69it/s] {'loss': 0.9982, 'grad_norm': 0.4508930444717407, 'learning_rate': 2.05e-05, 'epoch': 0.07} + 60%| | 60/100 [00:23<00:14, 2.69it/s] 61%| | 61/100 [00:23<00:15, 2.47it/s] 62%| | 62/100 [00:24<00:14, 2.67it/s] 63%| | 63/100 [00:24<00:12, 2.91it/s] 64%| | 64/100 [00:24<00:11, 3.14it/s] 65%| | 65/100 [00:25<00:13, 2.52it/s] 66%| | 66/100 [00:25<00:13, 2.52it/s] 67%| | 67/100 [00:25<00:11, 2.81it/s] 68%| | 68/100 [00:26<00:10, 2.97it/s] 69%| | 69/100 [00:26<00:11, 2.60it/s] 70%| | 70/100 [00:26<00:10, 2.73it/s] {'loss': 0.9991, 'grad_norm': 0.4352221190929413, 'learning_rate': 1.55e-05, 'epoch': 0.08} + 70%| | 70/100 [00:26<00:10, 2.73it/s] 71%| | 71/100 [00:27<00:09, 2.97it/s] 72%| | 72/100 [00:27<00:08, 3.25it/s] 73%| | 73/100 [00:27<00:09, 2.82it/s] 74%| | 74/100 [00:28<00:10, 2.37it/s] 75%| | 75/100 [00:28<00:09, 2.65it/s] 76%| | 76/100 [00:29<00:10, 2.34it/s] 77%| | 77/100 [00:29<00:09, 2.46it/s] 78%| | 78/100 [00:29<00:07, 2.86it/s] 79%| | 79/100 [00:30<00:06, 3.03it/s] 80%| | 80/100 [00:30<00:07, 2.60it/s] {'loss': 0.9537, 'grad_norm': 0.4679892361164093, 'learning_rate': 1.05e-05, 'epoch': 0.09} + 80%| | 80/100 [00:30<00:07, 2.60it/s] 81%| | 81/100 [00:30<00:06, 2.86it/s] 82%| | 82/100 [00:31<00:05, 3.04it/s] 83%| | 83/100 [00:31<00:05, 2.90it/s] 84%| | 84/100 [00:32<00:06, 2.48it/s] 85%| | 85/100 [00:32<00:05, 2.71it/s] 86%| | 86/100 [00:32<00:04, 2.91it/s] 87%| | 87/100 [00:33<00:04, 3.08it/s] 88%| | 88/100 [00:33<00:04, 2.66it/s] 89%| | 89/100 [00:33<00:03, 2.92it/s] 90%| | 90/100 [00:34<00:03, 2.97it/s] {'loss': 0.9677, 'grad_norm': 0.46999630331993103, 'learning_rate': 5.500000000000001e-06, 'epoch': 0.1} + 90%| | 90/100 [00:34<00:03, 2.97it/s] 91%| | 91/100 [00:34<00:02, 3.06it/s] 92%|| 92/100 [00:35<00:03, 2.11it/s] 93%|| 93/100 [00:35<00:03, 2.31it/s] 94%|| 94/100 [00:35<00:02, 2.46it/s] 95%|| 95/100 [00:36<00:02, 2.30it/s] 96%|| 96/100 [00:36<00:01, 2.56it/s] 97%|| 97/100 [00:36<00:01, 2.80it/s] 98%|| 98/100 [00:37<00:00, 2.77it/s] 99%|| 99/100 [00:37<00:00, 2.37it/s]100%|| 100/100 [00:38<00:00, 2.36it/s] {'loss': 0.9472, 'grad_norm': 0.45891430974006653, 'learning_rate': 5.000000000000001e-07, 'epoch': 0.11} +100%|| 100/100 [00:38<00:00, 2.36it/s][INFO|trainer.py:4309] 2025-10-22 17:18:17,492 >> Saving model checkpoint to /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-100 +[INFO|configuration_utils.py:765] 2025-10-22 17:18:17,662 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:839] 2025-10-22 17:18:17,663 >> Model config Qwen2Config { + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "dtype": "bfloat16", + "eos_token_id": 151643, + "hidden_act": "silu", + "hidden_size": 896, + "initializer_range": 0.02, + "intermediate_size": 4864, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 32768, + "max_window_layers": 24, + "model_type": "qwen2", + "num_attention_heads": 14, + "num_hidden_layers": 24, + "num_key_value_heads": 2, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 1000000.0, + "sliding_window": null, + "tie_word_embeddings": true, + "transformers_version": "4.57.1", + "use_cache": true, + "use_mrope": false, + "use_sliding_window": false, + "vocab_size": 151936 +} + +[INFO|tokenization_utils_base.py:2421] 2025-10-22 17:18:17,797 >> chat template saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-100/chat_template.jinja +[INFO|tokenization_utils_base.py:2590] 2025-10-22 17:18:17,803 >> tokenizer config file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-100/tokenizer_config.json +[INFO|tokenization_utils_base.py:2599] 2025-10-22 17:18:17,808 >> Special tokens file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-100/special_tokens_map.json +[INFO|trainer.py:2810] 2025-10-22 17:18:18,273 >> + +Training completed. Do not forget to share your model on huggingface.co/models =) + + + {'train_runtime': 40.2159, 'train_samples_per_second': 9.946, 'train_steps_per_second': 2.487, 'train_loss': 1.056060962677002, 'epoch': 0.11} +100%|| 100/100 [00:39<00:00, 2.36it/s]100%|| 100/100 [00:39<00:00, 2.55it/s] +[INFO|trainer.py:4309] 2025-10-22 17:18:18,283 >> Saving model checkpoint to /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints +[INFO|configuration_utils.py:765] 2025-10-22 17:18:18,362 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:839] 2025-10-22 17:18:18,363 >> Model config Qwen2Config { + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "dtype": "bfloat16", + "eos_token_id": 151643, + "hidden_act": "silu", + "hidden_size": 896, + "initializer_range": 0.02, + "intermediate_size": 4864, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 32768, + "max_window_layers": 24, + "model_type": "qwen2", + "num_attention_heads": 14, + "num_hidden_layers": 24, + "num_key_value_heads": 2, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 1000000.0, + "sliding_window": null, + "tie_word_embeddings": true, + "transformers_version": "4.57.1", + "use_cache": true, + "use_mrope": false, + "use_sliding_window": false, + "vocab_size": 151936 +} + +[INFO|tokenization_utils_base.py:2421] 2025-10-22 17:18:18,478 >> chat template saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/chat_template.jinja +[INFO|tokenization_utils_base.py:2590] 2025-10-22 17:18:18,483 >> tokenizer config file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/tokenizer_config.json +[INFO|tokenization_utils_base.py:2599] 2025-10-22 17:18:18,488 >> Special tokens file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/special_tokens_map.json +***** train metrics ***** + epoch = 0.1111 + total_flos = 2407106GF + train_loss = 1.0561 + train_runtime = 0:00:40.21 + train_samples_per_second = 9.946 + train_steps_per_second = 2.487 +[INFO|modelcard.py:456] 2025-10-22 17:18:18,662 >> Dropping the following result as it does not have all the necessary fields: +{'task': {'name': 'Causal Language Modeling', 'type': 'text-generation'}} +gl064:2405036:2405036 [1] NCCL INFO comm 0x16e337a0 rank 1 nranks 4 cudaDev 1 busId 59000 - Destroy COMPLETE +gl064:2405035:2405035 [0] NCCL INFO comm 0x1566a120 rank 0 nranks 4 cudaDev 0 busId 47000 - Destroy COMPLETE +[1;34mwandb[0m: +[1;34mwandb[0m: View run [33minteractive_test[0m at: [34m[0m +[1;34mwandb[0m: Find logs at: [1;35mwandb/run-20251022_171738-yru7qzfl/logs[0m + +======================================== +Training completed successfully +End Time: Wed Oct 22 05:18:20 PM EDT 2025 +======================================== + +======================================== +STAGE 2: Merging/Exporting Model +Start Time: Wed Oct 22 05:18:20 PM EDT 2025 +======================================== +Looking for checkpoints in: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints +Analyzing checkpoints to find the one from current training run... + - checkpoint-100: trainer_state.json modified at Wed Oct 22 05:18:18 PM EDT 2025 + - checkpoint-50: trainer_state.json modified at Wed Oct 22 05:17:58 PM EDT 2025 + +Selected checkpoint: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-100 +This checkpoint has the most recently updated trainer_state.json +Checkpoint details: + Path: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-100 + Last modified: 2025-10-22 16:54:17.414188691 -0400 + Training step: 100 +Updating merge config to point to checkpoint... +Successfully updated merge config +Updated merge config to use: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-100 + +Merge config contents: + model_name_or_path: Qwen/Qwen2.5-0.5B + finetuning_type: lora + trust_remote_code: true + adapter_name_or_path: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-100 + template: default + export_dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged + +Executing command: llamafactory-cli export /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/configs/merge_config.yaml +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/scratch/zrs2020/miniconda/miniconda3/envs/llamafactory/lib/python3.12/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. + import pkg_resources +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,229 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,229 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,229 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,229 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,229 >> loading file special_tokens_map.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,229 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,229 >> loading file chat_template.jinja from cache at None +[INFO|tokenization_utils_base.py:2364] 2025-10-22 17:18:31,401 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +[INFO|configuration_utils.py:765] 2025-10-22 17:18:31,605 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:839] 2025-10-22 17:18:31,608 >> Model config Qwen2Config { + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "dtype": "bfloat16", + "eos_token_id": 151643, + "hidden_act": "silu", + "hidden_size": 896, + "initializer_range": 0.02, + "intermediate_size": 4864, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 32768, + "max_window_layers": 24, + "model_type": "qwen2", + "num_attention_heads": 14, + "num_hidden_layers": 24, + "num_key_value_heads": 2, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 1000000.0, + "sliding_window": null, + "tie_word_embeddings": true, + "transformers_version": "4.57.1", + "use_cache": true, + "use_mrope": false, + "use_sliding_window": false, + "vocab_size": 151936 +} + +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,670 >> loading file vocab.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/vocab.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,670 >> loading file merges.txt from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/merges.txt +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,670 >> loading file tokenizer.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,670 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,670 >> loading file special_tokens_map.json from cache at None +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,670 >> loading file tokenizer_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/tokenizer_config.json +[INFO|tokenization_utils_base.py:2095] 2025-10-22 17:18:31,670 >> loading file chat_template.jinja from cache at None +[INFO|tokenization_utils_base.py:2364] 2025-10-22 17:18:31,838 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +[INFO|configuration_utils.py:765] 2025-10-22 17:18:31,887 >> loading configuration file config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/config.json +[INFO|configuration_utils.py:839] 2025-10-22 17:18:31,887 >> Model config Qwen2Config { + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "dtype": "bfloat16", + "eos_token_id": 151643, + "hidden_act": "silu", + "hidden_size": 896, + "initializer_range": 0.02, + "intermediate_size": 4864, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 32768, + "max_window_layers": 24, + "model_type": "qwen2", + "num_attention_heads": 14, + "num_hidden_layers": 24, + "num_key_value_heads": 2, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 1000000.0, + "sliding_window": null, + "tie_word_embeddings": true, + "transformers_version": "4.57.1", + "use_cache": true, + "use_mrope": false, + "use_sliding_window": false, + "vocab_size": 151936 +} + +[WARNING|logging.py:328] 2025-10-22 17:18:31,887 >> `torch_dtype` is deprecated! Use `dtype` instead! +[INFO|2025-10-22 17:18:31] llamafactory.model.model_utils.kv_cache:143 >> KV cache is enabled for faster generation. +[WARNING|logging.py:328] 2025-10-22 17:18:32,222 >> `torch_dtype` is deprecated! Use `dtype` instead! +[INFO|modeling_utils.py:1172] 2025-10-22 17:18:32,223 >> loading weights file model.safetensors from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/model.safetensors +[INFO|modeling_utils.py:2341] 2025-10-22 17:18:32,224 >> Instantiating Qwen2ForCausalLM model under default dtype torch.bfloat16. +[INFO|configuration_utils.py:986] 2025-10-22 17:18:32,224 >> Generate config GenerationConfig { + "bos_token_id": 151643, + "eos_token_id": 151643 +} + +[INFO|configuration_utils.py:941] 2025-10-22 17:18:32,323 >> loading configuration file generation_config.json from cache at /scratch/zrs2020/.cache/hf_cache/home/hub/models--Qwen--Qwen2.5-0.5B/snapshots/060db6499f32faf8b98477b0a26969ef7d8b9987/generation_config.json +[INFO|configuration_utils.py:986] 2025-10-22 17:18:32,323 >> Generate config GenerationConfig { + "bos_token_id": 151643, + "eos_token_id": 151643, + "max_new_tokens": 2048 +} + +[INFO|dynamic_module_utils.py:423] 2025-10-22 17:18:32,355 >> Could not locate the custom_generate/generate.py inside Qwen/Qwen2.5-0.5B. +[INFO|2025-10-22 17:18:32] llamafactory.model.model_utils.attention:143 >> Using torch SDPA for faster training and inference. +[INFO|2025-10-22 17:18:33] llamafactory.model.adapter:143 >> Merged 1 adapter(s). +[INFO|2025-10-22 17:18:33] llamafactory.model.adapter:143 >> Loaded adapter(s): /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-100 +[INFO|2025-10-22 17:18:33] llamafactory.model.loader:143 >> all params: 494,032,768 +[INFO|2025-10-22 17:18:33] llamafactory.train.tuner:143 >> Convert model dtype to: torch.bfloat16. +[INFO|configuration_utils.py:491] 2025-10-22 17:18:33,183 >> Configuration saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged/config.json +[INFO|configuration_utils.py:757] 2025-10-22 17:18:33,187 >> Configuration saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged/generation_config.json +[INFO|modeling_utils.py:4181] 2025-10-22 17:18:34,845 >> Model weights saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged/model.safetensors +[INFO|tokenization_utils_base.py:2421] 2025-10-22 17:18:34,851 >> chat template saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged/chat_template.jinja +[INFO|tokenization_utils_base.py:2590] 2025-10-22 17:18:34,856 >> tokenizer config file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged/tokenizer_config.json +[INFO|tokenization_utils_base.py:2599] 2025-10-22 17:18:34,860 >> Special tokens file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged/special_tokens_map.json +[INFO|2025-10-22 17:18:35] llamafactory.train.tuner:143 >> Ollama modelfile saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged/Modelfile + +======================================== +Merge/Export completed successfully +End Time: Wed Oct 22 05:18:35 PM EDT 2025 +======================================== + +======================================== +Preparing Training Artifacts +======================================== +Copying configuration files... +Copying and cleaning training logs...