Upload folder using huggingface_hub

.gitattributes

@@ -1,36 +1,8 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ckpt filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.mlmodel filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.npy filter=lfs diff=lfs merge=lfs -text
-*.npz filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pickle filter=lfs diff=lfs merge=lfs -text
-*.pkl filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-*.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
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-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Mark all log files as text to prevent binary file issues
+*.log text
+*.txt text
+*.out text
+*.err text
+training_artifacts/logs/* text
+model.safetensors filter=lfs diff=lfs merge=lfs -text
 tokenizer.json filter=lfs diff=lfs merge=lfs -text

model.safetensors

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 size 988097824

training_artifacts/README.md

@@ -0,0 +1,16 @@
+# Training Artifacts
+
+This directory contains the training configuration and logs for this model.
+
+## Contents
+
+- **hydra_config.yaml**: Complete Hydra configuration used for training
+- **train_config.yaml**: LlamaFactory training configuration
+- **merge_config.yaml**: LlamaFactory merge/export configuration
+- **logs/**: Training logs from the job (cleaned for text format)
+
+## Job Information
+
+- Job Name: lf_torch_test__interactive
+- Timestamp: 2025-10-22 20:02:45 UTC
+- Execution Mode: Local

training_artifacts/hydra_config.yaml

@@ -0,0 +1,216 @@
+? ''
+: ? ''
+  : ? ''
+    : hydra:
+        run:
+          dir: .
+        output_subdir: null
+        job:
+          chdir: false
+      _target_: null
+      job:
+        name: ???
+        mode: slurm
+        work_dir: null
+        dry_run: false
+      slurm:
+        time_limit: ???
+        constraint:
+        - h200
+        memory: 200
+        cpus_per_task: 16
+        partition: null
+        mail_user: user@example.com
+      execution:
+        nodes: null
+        gpus_per_node: null
+        num_gpus: null
+        hostfile: null
+        secrets_file: null
+      model:
+        name_or_path: ???
+        finetuning_type: lora
+      dataset:
+        name: ???
+        dir: null
+        info_json: null
+        template: default
+        cutoff_len: 1024
+        val_size: 0.1
+        hf_hub_url: null
+        formatting: alpaca
+        ranking: false
+        subset: null
+        split: train
+        folder: null
+        num_samples: null
+        columns:
+          prompt: null
+          query: null
+          response: null
+          history: null
+          messages: null
+          system: null
+          tools: null
+          images: null
+          videos: null
+          audios: null
+          chosen: null
+          rejected: null
+          kto_tag: null
+        tags:
+          role: null
+          content: null
+          user: null
+          assistant: null
+          observation: null
+          function: null
+          system: null
+      training:
+        stage: sft
+        do_train: true
+        model_name_or_path: null
+        finetuning_type: lora
+        trust_remote_code: true
+        dataset: null
+        dataset_dir: null
+        template: default
+        cutoff_len: 1024
+        val_size: 0.1
+        preprocessing_num_workers: 1
+        dataset_num_proc: 1
+        dataloader_num_workers: 0
+        streaming: false
+        learning_rate: 5.0e-05
+        num_train_epochs: 3.0
+        per_device_train_batch_size: 1
+        per_device_eval_batch_size: 1
+        gradient_accumulation_steps: 8
+        lr_scheduler_type: cosine
+        warmup_ratio: 0.1
+        warmup_steps: 0
+        lora_rank: 8
+        lora_alpha: 16
+        lora_dropout: 0.05
+        lora_target: all
+        optim: adamw_torch
+        bf16: true
+        fp16: false
+        output_dir: null
+        save_strategy: epoch
+        save_steps: 500
+        save_total_limit: 3
+        save_only_model: false
+        eval_strategy: steps
+        eval_steps: 500
+        do_eval: true
+        logging_steps: 10
+        plot_loss: true
+        report_to: none
+        gradient_checkpointing: true
+        ddp_timeout: 180000000
+        include_num_input_tokens_seen: true
+        overwrite_output_dir: true
+        overwrite_cache: false
+        seed: 42
+      lora:
+        rank: 8
+        alpha: 16
+        dropout: 0.05
+        target: all
+      output:
+        experiment_dir: ./experiments
+      merge:
+        stage: export
+        model_name_or_path: null
+        adapter_name_or_path: null
+        template: default
+        export_dir: null
+        export_size: 2
+        export_device: auto
+        export_legacy_format: false
+        finetuning_type: lora
+      wandb:
+        project: null
+        run_name: null
+        entity: null
+      hf:
+        repo_id: null
+        private: false
+        upload_artifacts: true
+      cleanup:
+        checkpoints: false
+        merged: false
+job:
+  name: lf_torch_test__interactive
+  mode: local
+  work_dir: null
+  dry_run: false
+slurm:
+  time_limit: null
+  constraint: null
+  memory: null
+  partition: null
+  mail_user: null
+execution:
+  nodes: 2
+  gpus_per_node: 2
+  num_gpus: null
+  hostfile: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/hostfile_auto_generated.txt
+  secrets_file: ./secrets.env
+model:
+  name_or_path: Qwen/Qwen2.5-0.5B
+  finetuning_type: lora
+lora:
+  rank: 8
+  alpha: 16
+  dropout: 0.05
+  target: all
+dataset:
+  name: my_custom_sft
+  dir: null
+  info_json: null
+  template: default
+  cutoff_len: 8096
+  val_size: 0.1
+  hf_hub_url: TAUR-dev/D-SFT_C-sft_exp_AT_pvv2__fixed-sft-data
+  formatting: sharegpt
+  ranking: false
+  subset: null
+  split: train
+  folder: null
+  num_samples: null
+  columns:
+    messages: conversations
+  tags:
+    role: role
+    content: content
+    user: user
+    assistant: assistant
+output:
+  experiment_dir: ./experiments
+wandb:
+  project: null
+  run_name: interactive_test
+  entity: null
+hf:
+  repo_id: TAUR-dev/testing_llamafactory_helper_quick_test__interactive
+  private: false
+cleanup:
+  checkpoints: false
+  merged: false
+training:
+  stage: sft
+  do_train: true
+  max_steps: 150
+  do_eval: false
+  save_strategy: steps
+  save_steps: 50
+  logging_steps: 10
+  fp16: true
+  bf16: false
+  overwrite_output_dir: true
+  per_device_train_batch_size: 1
+  gradient_accumulation_steps: 1
+  gradient_checkpointing: true
+merge: {}

training_artifacts/logs/pipeline_cleaned.txt

@@ -0,0 +1,1050 @@
+========================================
+Job Name: lf_torch_test__interactive
+Hostname: gl064.hpc.nyu.edu
+Number of nodes: 2
+GPUs per node: 2
+Start Time: Wed Oct 22 04:01:29 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 04:01:31 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(
+/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 16:01:48] llamafactory.hparams.parser:423 >> Process rank: 1, world size: 4, device: cuda:1, distributed training: True, compute dtype: torch.float16
+[INFO|2025-10-22 16:01:48] llamafactory.hparams.parser:143 >> Set `ddp_find_unused_parameters` to False in DDP training since LoRA is enabled.
+[INFO|2025-10-22 16:01:48] llamafactory.hparams.parser:423 >> Process rank: 0, world size: 4, device: cuda:0, distributed training: True, compute dtype: torch.float16
+[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:01:48,287 >> 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 16:01:48,287 >> 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 16:01:48,288 >> 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 16:01:48,288 >> loading file added_tokens.json from cache at None
+[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:01:48,288 >> loading file special_tokens_map.json from cache at None
+[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:01:48,288 >> 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 16:01:48,288 >> loading file chat_template.jinja from cache at None
+[INFO|tokenization_utils_base.py:2364] 2025-10-22 16:01:48,457 >> 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 16:01:48,674 >> 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 16:01:48,676 >> 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 16:01:48,738 >> 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 16:01:48,738 >> 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 16:01:48,738 >> 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 16:01:48,738 >> loading file added_tokens.json from cache at None
+[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:01:48,738 >> loading file special_tokens_map.json from cache at None
+[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:01:48,738 >> 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 16:01:48,738 >> loading file chat_template.jinja from cache at None
+[INFO|tokenization_utils_base.py:2364] 2025-10-22 16:01:48,904 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
+[INFO|2025-10-22 16:01:48] 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 16:01:49.085275271 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()
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+training example:
+input_ids:
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+inputs:
+Human: Answer the following problem. Explain your reasoning step by step. When you are finished, give your answer in this format: <answer>(your answer)</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:
+<answer>
+(your answer)
+</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:
+<answer>
+Step 1: 1 + 2 = 3
+Step 2: 3 / 3 = 1
+</answer>
+
+or 
+
+<answer>
+(1 + 2) / 3
+</answer>
+
+Let's think step by step.<|endoftext|>
+Assistant:<think>
+<sample>
+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:
+
+<answer>
+(67 * 2) + 71 - 31
+</answer>
+</sample>
+<reflect>
+Let us verify this answer:
+
+First, 67 + 71 = 138, then 138 - 31 = 107. This does not equal 169, so the answer is incorrect.
+
+<verdict>
+Incorrect
+</verdict>
+</reflect>
+Let me verify my answer.
+<sample>
+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.
+
+<answer>
+(67 * 31) + 71 = 169
+</answer>
+</sample>
+<reflect>
+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.
+
+<verdict>
+Incorrect
+</verdict>
+</reflect>
+Time to review my response one more time.
+<sample>
+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 "<answer>
+(your answer)
+</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 "<answer>
+(your answer)
+</answer>" format.
+
+Now let me begin searching for the correct combination!
+</sample>
+<reflect>
+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.
+
+<verdict>
+Incorrect
+</verdict>
+</reflect>
+But wait, let me think about it again.
+<sample>
+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
+
+<answer>
+(67 + 31) + 71
+</answer>
+</sample>
+<reflect>
+Let us verify this answer: First, 67 + 31 = 98, then 98 + 71 = 169. The answer is correct.
+
+<verdict>
+Correct
+</verdict>
+</reflect>
+</think>
+
+
+Hence, the correct answer is:
+
+<answer>
+(67 + 31) + 71
+</answer><|endoftext|>
+
+label_ids:
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264, 3119, 323, 728, 2167, 5538, 1119, 7716, 911, 1246, 358, 1265, 11625, 419, 624, 785, 5795, 374, 311, 1855, 458, 23606, 1667, 279, 5109, 220, 21, 22, 11, 220, 22, 16, 11, 323, 220, 18, 16, 429, 16819, 220, 16, 21, 24, 624, 40, 686, 1191, 553, 4460, 2155, 27459, 315, 1493, 2326, 5109, 323, 862, 3204, 7525, 17973, 11, 85922, 11777, 608, 568, 715, 12209, 358, 686, 15442, 1817, 10601, 323, 1779, 421, 807, 6144, 220, 16, 21, 24, 13, 1416, 537, 11, 358, 686, 3271, 389, 311, 279, 1790, 10601, 3080, 358, 1477, 825, 429, 4278, 624, 6025, 9271, 279, 4396, 10601, 11, 358, 686, 3042, 847, 6291, 304, 279, 4055, 9217, 397, 7021, 413, 4226, 340, 522, 9217, 9877, 3561, 624, 8420, 594, 847, 11682, 3119, 1447, 16, 13, 4230, 678, 3204, 27459, 315, 220, 21, 22, 11, 220, 22, 16, 11, 323, 220, 18, 16, 1667, 5256, 11, 75240, 11, 46444, 11, 323, 12804, 624, 17, 13, 54115, 1817, 10601, 311, 1490, 421, 432, 16819, 220, 16, 21, 24, 624, 18, 13, 1416, 902, 10601, 16819, 220, 16, 21, 24, 11, 13153, 279, 1882, 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220, 18, 16, 624, 8304, 220, 17, 25, 11778, 279, 2629, 504, 14822, 220, 16, 323, 912, 220, 22, 16, 382, 19357, 84670, 25, 320, 21, 22, 488, 220, 18, 16, 8, 488, 220, 22, 16, 271, 27, 9217, 397, 7, 21, 22, 488, 220, 18, 16, 8, 488, 220, 22, 16, 198, 522, 9217, 397, 522, 13611, 397, 27, 34913, 397, 10061, 601, 10146, 419, 4226, 25, 5512, 11, 220, 21, 22, 488, 220, 18, 16, 284, 220, 24, 23, 11, 1221, 220, 24, 23, 488, 220, 22, 16, 284, 220, 16, 21, 24, 13, 576, 4226, 374, 4396, 382, 27, 423, 8477, 397, 33092, 198, 522, 423, 8477, 397, 522, 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]
+labels:
+<think>
+<sample>
+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:
+
+<answer>
+(67 * 2) + 71 - 31
+</answer>
+</sample>
+<reflect>
+Let us verify this answer:
+
+First, 67 + 71 = 138, then 138 - 31 = 107. This does not equal 169, so the answer is incorrect.
+
+<verdict>
+Incorrect
+</verdict>
+</reflect>
+Let me verify my answer.
+<sample>
+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.
+
+<answer>
+(67 * 31) + 71 = 169
+</answer>
+</sample>
+<reflect>
+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.
+
+<verdict>
+Incorrect
+</verdict>
+</reflect>
+Time to review my response one more time.
+<sample>
+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 "<answer>
+(your answer)
+</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 "<answer>
+(your answer)
+</answer>" format.
+
+Now let me begin searching for the correct combination!
+</sample>
+<reflect>
+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.
+
+<verdict>
+Incorrect
+</verdict>
+</reflect>
+But wait, let me think about it again.
+<sample>
+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
+
+<answer>
+(67 + 31) + 71
+</answer>
+</sample>
+<reflect>
+Let us verify this answer: First, 67 + 31 = 98, then 98 + 71 = 169. The answer is correct.
+
+<verdict>
+Correct
+</verdict>
+</reflect>
+</think>
+
+
+Hence, the correct answer is:
+
+<answer>
+(67 + 31) + 71
+</answer><|endoftext|>
+
+[INFO|configuration_utils.py:765] 2025-10-22 16:01:50,484 >> 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 16:01:50,485 >> 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 16:01:50] llamafactory.model.model_utils.kv_cache:143 >> KV cache is disabled during training.
+[WARNING|logging.py:328] 2025-10-22 16:01:50,806 >> `torch_dtype` is deprecated! Use `dtype` instead!
+[INFO|modeling_utils.py:1172] 2025-10-22 16:01:50,807 >> 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 16:01:50,808 >> Instantiating Qwen2ForCausalLM model under default dtype torch.float16.
+[INFO|configuration_utils.py:986] 2025-10-22 16:01:50,808 >> 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 16:01:51,084 >> 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 16:01:51,085 >> Generate config GenerationConfig {
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048
+}
+
+[INFO|dynamic_module_utils.py:423] 2025-10-22 16:01:51,114 >> Could not locate the custom_generate/generate.py inside Qwen/Qwen2.5-0.5B.
+[INFO|2025-10-22 16:01:51] llamafactory.model.model_utils.checkpointing:143 >> Gradient checkpointing enabled.
+[INFO|2025-10-22 16:01:51] llamafactory.model.model_utils.attention:143 >> Using torch SDPA for faster training and inference.
+[INFO|2025-10-22 16:01:51] llamafactory.model.adapter:143 >> Upcasting trainable params to float32.
+[INFO|2025-10-22 16:01:51] llamafactory.model.adapter:143 >> Fine-tuning method: LoRA
+[INFO|2025-10-22 16:01:51] llamafactory.model.model_utils.misc:143 >> Found linear modules: up_proj,v_proj,q_proj,down_proj,gate_proj,k_proj,o_proj
+[INFO|2025-10-22 16:01:51] llamafactory.model.loader:143 >> trainable params: 4,399,104 || all params: 498,431,872 || trainable%: 0.8826
+[WARNING|trainer.py:906] 2025-10-22 16:01:51,639 >> The model is already on multiple devices. Skipping the move to device specified in `args`.
+[INFO|trainer.py:699] 2025-10-22 16:01:51,642 >> max_steps is given, it will override any value given in num_train_epochs
+[INFO|trainer.py:749] 2025-10-22 16:01:51,642 >> Using auto half precision backend
+[WARNING|trainer.py:982] 2025-10-22 16:01:51,643 >> 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 16:01:51,823 >> ***** Running training *****
+[INFO|trainer.py:2520] 2025-10-22 16:01:51,823 >>   Num examples = 48,600
+[INFO|trainer.py:2521] 2025-10-22 16:01:51,823 >>   Num Epochs = 1
+[INFO|trainer.py:2522] 2025-10-22 16:01:51,823 >>   Instantaneous batch size per device = 1
+[INFO|trainer.py:2525] 2025-10-22 16:01:51,823 >>   Total train batch size (w. parallel, distributed & accumulation) = 4
+[INFO|trainer.py:2526] 2025-10-22 16:01:51,823 >>   Gradient Accumulation steps = 1
+[INFO|trainer.py:2527] 2025-10-22 16:01:51,823 >>   Total optimization steps = 150
+[INFO|trainer.py:2528] 2025-10-22 16:01:51,825 >>   Number of trainable parameters = 4,399,104
+[INFO|integration_utils.py:867] 2025-10-22 16:01:51,847 >> 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_160152-f7vqjhyf
+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/f7vqjhyf
+  0%|          | 0/150 [00:00<?, ?it/s]  1%|          | 1/150 [00:00<01:26,  1.72it/s]  1%|         | 2/150 [00:00<00:50,  2.95it/s]  2%|         | 3/150 [00:00<00:37,  3.88it/s]  3%|         | 4/150 [00:01<00:35,  4.09it/s]  3%|         | 5/150 [00:01<00:54,  2.68it/s]  4%|         | 6/150 [00:01<00:47,  3.02it/s]  5%|         | 7/150 [00:02<00:43,  3.27it/s]  5%|         | 8/150 [00:02<00:38,  3.65it/s]  6%|         | 9/150 [00:02<00:35,  3.92it/s]  7%|         | 10/150 [00:02<00:32,  4.32it/s]                                                {'loss': 0.8092, 'grad_norm': 0.4081718623638153, 'learning_rate': 4.7e-05, 'epoch': 0.0}
+  7%|         | 10/150 [00:02<00:32,  4.32it/s]  7%|         | 11/150 [00:03<00:31,  4.39it/s]  8%|         | 12/150 [00:03<00:41,  3.29it/s]  9%|         | 13/150 [00:03<00:35,  3.88it/s]  9%|         | 14/150 [00:03<00:30,  4.43it/s] 10%|         | 15/150 [00:04<00:28,  4.78it/s] 11%|         | 16/150 [00:04<00:37,  3.59it/s] 11%|        | 17/150 [00:04<00:36,  3.62it/s] 12%|        | 18/150 [00:04<00:35,  3.69it/s] 13%|        | 19/150 [00:05<00:35,  3.69it/s] 13%|        | 20/150 [00:05<00:32,  3.98it/s]                                                {'loss': 0.751, 'grad_norm': 0.3975396752357483, 'learning_rate': 4.3666666666666666e-05, 'epoch': 0.0}
+ 13%|        | 20/150 [00:05<00:32,  3.98it/s] 14%|        | 21/150 [00:05<00:32,  3.94it/s] 15%|        | 22/150 [00:05<00:30,  4.18it/s] 15%|        | 23/150 [00:06<00:31,  4.07it/s] 16%|        | 24/150 [00:06<00:28,  4.40it/s] 17%|        | 25/150 [00:06<00:31,  4.02it/s] 17%|        | 26/150 [00:06<00:29,  4.17it/s] 18%|        | 27/150 [00:07<00:30,  4.10it/s] 19%|        | 28/150 [00:07<00:33,  3.65it/s] 19%|        | 29/150 [00:07<00:32,  3.75it/s] 20%|        | 30/150 [00:07<00:31,  3.85it/s]                                                {'loss': 0.7344, 'grad_norm': 0.46849244832992554, 'learning_rate': 4.0333333333333336e-05, 'epoch': 0.0}
+ 20%|        | 30/150 [00:07<00:31,  3.85it/s] 21%|        | 31/150 [00:08<00:31,  3.83it/s] 21%|       | 32/150 [00:08<00:29,  4.05it/s] 22%|       | 33/150 [00:08<00:26,  4.43it/s] 23%|       | 34/150 [00:08<00:23,  4.87it/s] 23%|       | 35/150 [00:09<00:25,  4.58it/s] 24%|       | 36/150 [00:09<00:22,  5.04it/s] 25%|       | 37/150 [00:09<00:24,  4.71it/s] 25%|       | 38/150 [00:09<00:24,  4.67it/s] 26%|       | 39/150 [00:09<00:22,  4.98it/s] 27%|       | 40/150 [00:10<00:23,  4.58it/s]                                                {'loss': 0.7063, 'grad_norm': 0.3817349970340729, 'learning_rate': 3.7e-05, 'epoch': 0.0}
+ 27%|       | 40/150 [00:10<00:23,  4.58it/s] 27%|       | 41/150 [00:10<00:26,  4.09it/s] 28%|       | 42/150 [00:10<00:26,  4.07it/s] 29%|       | 43/150 [00:10<00:23,  4.58it/s] 29%|       | 44/150 [00:10<00:21,  4.90it/s] 30%|       | 45/150 [00:11<00:19,  5.33it/s] 31%|       | 46/150 [00:11<00:20,  4.98it/s] 31%|      | 47/150 [00:11<00:21,  4.88it/s] 32%|      | 48/150 [00:11<00:19,  5.14it/s] 33%|      | 49/150 [00:12<00:22,  4.50it/s] 33%|      | 50/150 [00:12<00:22,  4.49it/s]                                                {'loss': 0.6382, 'grad_norm': 0.650374710559845, 'learning_rate': 3.366666666666667e-05, 'epoch': 0.0}
+ 33%|      | 50/150 [00:12<00:22,  4.49it/s][INFO|trainer.py:4309] 2025-10-22 16:02:05,111 >> Saving model checkpoint to /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-50
+[INFO|configuration_utils.py:765] 2025-10-22 16:02:05,262 >> 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 16:02:05,263 >> 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 16:02:05,402 >> 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 16:02:05,406 >> 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 16:02:05,410 >> Special tokens file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-50/special_tokens_map.json
+ 34%|      | 51/150 [00:13<00:44,  2.20it/s] 35%|      | 52/150 [00:13<00:39,  2.47it/s] 35%|      | 53/150 [00:13<00:34,  2.82it/s] 36%|      | 54/150 [00:13<00:28,  3.40it/s] 37%|      | 55/150 [00:14<00:27,  3.45it/s] 37%|      | 56/150 [00:14<00:23,  4.06it/s] 38%|      | 57/150 [00:14<00:22,  4.10it/s] 39%|      | 58/150 [00:14<00:20,  4.51it/s] 39%|      | 59/150 [00:14<00:17,  5.19it/s] 40%|      | 60/150 [00:15<00:16,  5.57it/s]                                                {'loss': 0.6139, 'grad_norm': 0.4990316331386566, 'learning_rate': 3.0333333333333337e-05, 'epoch': 0.0}
+ 40%|      | 60/150 [00:15<00:16,  5.57it/s] 41%|      | 61/150 [00:15<00:17,  5.19it/s] 41%|     | 62/150 [00:15<00:15,  5.74it/s] 42%|     | 63/150 [00:15<00:16,  5.17it/s] 43%|     | 64/150 [00:15<00:15,  5.45it/s] 43%|     | 65/150 [00:16<00:17,  4.97it/s] 44%|     | 66/150 [00:16<00:18,  4.59it/s] 45%|     | 67/150 [00:16<00:17,  4.86it/s] 45%|     | 68/150 [00:16<00:18,  4.54it/s] 46%|     | 69/150 [00:16<00:19,  4.15it/s] 47%|     | 70/150 [00:17<00:19,  4.10it/s]                                                {'loss': 0.597, 'grad_norm': 0.5236718058586121, 'learning_rate': 2.7000000000000002e-05, 'epoch': 0.01}
+ 47%|     | 70/150 [00:17<00:19,  4.10it/s] 47%|     | 71/150 [00:17<00:19,  3.97it/s] 48%|     | 72/150 [00:17<00:17,  4.48it/s] 49%|     | 73/150 [00:17<00:19,  4.00it/s] 49%|     | 74/150 [00:18<00:18,  4.19it/s] 50%|     | 75/150 [00:18<00:15,  4.70it/s] 51%|     | 76/150 [00:18<00:15,  4.73it/s] 51%|    | 77/150 [00:18<00:13,  5.23it/s] 52%|    | 78/150 [00:18<00:15,  4.68it/s] 53%|    | 79/150 [00:19<00:15,  4.55it/s] 53%|    | 80/150 [00:19<00:16,  4.27it/s]                                                {'loss': 0.6205, 'grad_norm': 0.41710713505744934, 'learning_rate': 2.3666666666666668e-05, 'epoch': 0.01}
+ 53%|    | 80/150 [00:19<00:16,  4.27it/s] 54%|    | 81/150 [00:19<00:14,  4.65it/s] 55%|    | 82/150 [00:19<00:16,  4.06it/s] 55%|    | 83/150 [00:20<00:15,  4.45it/s] 56%|    | 84/150 [00:20<00:15,  4.39it/s] 57%|    | 85/150 [00:20<00:14,  4.45it/s] 57%|    | 86/150 [00:20<00:12,  5.07it/s] 58%|    | 87/150 [00:20<00:12,  5.19it/s] 59%|    | 88/150 [00:21<00:12,  4.88it/s] 59%|    | 89/150 [00:21<00:13,  4.59it/s] 60%|    | 90/150 [00:21<00:11,  5.22it/s]                                                {'loss': 0.6038, 'grad_norm': 0.5673879981040955, 'learning_rate': 2.0333333333333334e-05, 'epoch': 0.01}
+ 60%|    | 90/150 [00:21<00:11,  5.22it/s] 61%|    | 91/150 [00:21<00:12,  4.64it/s] 61%|   | 92/150 [00:22<00:12,  4.53it/s] 62%|   | 93/150 [00:22<00:12,  4.75it/s] 63%|   | 94/150 [00:22<00:11,  4.69it/s] 63%|   | 95/150 [00:22<00:11,  4.78it/s] 64%|   | 96/150 [00:22<00:12,  4.42it/s] 65%|   | 97/150 [00:23<00:13,  3.84it/s] 65%|   | 98/150 [00:23<00:12,  4.26it/s] 66%|   | 99/150 [00:23<00:11,  4.53it/s] 67%|   | 100/150 [00:23<00:11,  4.31it/s]                                                 {'loss': 0.5934, 'grad_norm': 0.49819639325141907, 'learning_rate': 1.7000000000000003e-05, 'epoch': 0.01}
+ 67%|   | 100/150 [00:23<00:11,  4.31it/s][INFO|trainer.py:4309] 2025-10-22 16:02:16,719 >> Saving model checkpoint to /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-100
+[INFO|configuration_utils.py:765] 2025-10-22 16:02:16,928 >> 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 16:02:16,929 >> 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 16:02:17,110 >> 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 16:02:17,130 >> 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 16:02:17,134 >> Special tokens file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-100/special_tokens_map.json
+ 67%|   | 101/150 [00:25<00:25,  1.91it/s] 68%|   | 102/150 [00:25<00:21,  2.24it/s] 69%|   | 103/150 [00:25<00:17,  2.71it/s] 69%|   | 104/150 [00:25<00:18,  2.54it/s] 70%|   | 105/150 [00:26<00:17,  2.56it/s] 71%|   | 106/150 [00:26<00:16,  2.71it/s] 71%|  | 107/150 [00:26<00:14,  2.87it/s] 72%|  | 108/150 [00:27<00:12,  3.30it/s] 73%|  | 109/150 [00:27<00:11,  3.59it/s] 73%|  | 110/150 [00:27<00:10,  3.89it/s]                                                 {'loss': 0.5548, 'grad_norm': 0.48188939690589905, 'learning_rate': 1.3666666666666666e-05, 'epoch': 0.01}
+ 73%|  | 110/150 [00:27<00:10,  3.89it/s] 74%|  | 111/150 [00:27<00:10,  3.80it/s] 75%|  | 112/150 [00:28<00:08,  4.25it/s] 75%|  | 113/150 [00:28<00:08,  4.41it/s] 76%|  | 114/150 [00:28<00:07,  4.81it/s] 77%|  | 115/150 [00:28<00:08,  4.33it/s] 77%|  | 116/150 [00:29<00:09,  3.70it/s] 78%|  | 117/150 [00:29<00:07,  4.23it/s] 79%|  | 118/150 [00:29<00:06,  4.74it/s] 79%|  | 119/150 [00:29<00:06,  4.49it/s] 80%|  | 120/150 [00:29<00:06,  4.79it/s]                                                 {'loss': 0.5132, 'grad_norm': 0.5217602252960205, 'learning_rate': 1.0333333333333333e-05, 'epoch': 0.01}
+ 80%|  | 120/150 [00:29<00:06,  4.79it/s] 81%|  | 121/150 [00:30<00:06,  4.48it/s] 81%| | 122/150 [00:30<00:05,  4.81it/s] 82%| | 123/150 [00:30<00:05,  5.05it/s] 83%| | 124/150 [00:30<00:05,  4.71it/s] 83%| | 125/150 [00:30<00:05,  4.71it/s] 84%| | 126/150 [00:31<00:05,  4.01it/s] 85%| | 127/150 [00:31<00:05,  3.95it/s] 85%| | 128/150 [00:31<00:05,  4.01it/s] 86%| | 129/150 [00:31<00:05,  3.99it/s] 87%| | 130/150 [00:32<00:04,  4.54it/s]                                                 {'loss': 0.5586, 'grad_norm': 0.8095545172691345, 'learning_rate': 7.000000000000001e-06, 'epoch': 0.01}
+ 87%| | 130/150 [00:32<00:04,  4.54it/s] 87%| | 131/150 [00:32<00:04,  4.34it/s] 88%| | 132/150 [00:32<00:03,  4.82it/s] 89%| | 133/150 [00:32<00:03,  4.39it/s] 89%| | 134/150 [00:33<00:03,  4.06it/s] 90%| | 135/150 [00:33<00:03,  3.91it/s] 91%| | 136/150 [00:33<00:03,  4.34it/s] 91%|| 137/150 [00:33<00:02,  4.52it/s] 92%|| 138/150 [00:33<00:02,  4.40it/s] 93%|| 139/150 [00:34<00:02,  3.95it/s] 93%|| 140/150 [00:34<00:02,  4.35it/s]                                                 {'loss': 0.563, 'grad_norm': 0.4983977973461151, 'learning_rate': 3.666666666666667e-06, 'epoch': 0.01}
+ 93%|| 140/150 [00:34<00:02,  4.35it/s] 94%|| 141/150 [00:34<00:02,  4.24it/s] 95%|| 142/150 [00:34<00:01,  4.53it/s] 95%|| 143/150 [00:35<00:01,  4.31it/s] 96%|| 144/150 [00:35<00:01,  4.96it/s] 97%|| 145/150 [00:35<00:01,  4.96it/s] 97%|| 146/150 [00:35<00:00,  4.70it/s] 98%|| 147/150 [00:35<00:00,  5.18it/s] 99%|| 148/150 [00:36<00:00,  5.32it/s] 99%|| 149/150 [00:36<00:00,  5.52it/s]100%|| 150/150 [00:36<00:00,  4.81it/s]                                                 {'loss': 0.5749, 'grad_norm': 0.4249863624572754, 'learning_rate': 3.3333333333333335e-07, 'epoch': 0.01}
+100%|| 150/150 [00:36<00:00,  4.81it/s][INFO|trainer.py:4309] 2025-10-22 16:02:29,334 >> Saving model checkpoint to /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-150
+[INFO|configuration_utils.py:765] 2025-10-22 16:02:29,507 >> 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 16:02:29,508 >> 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 16:02:29,679 >> chat template saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-150/chat_template.jinja
+[INFO|tokenization_utils_base.py:2590] 2025-10-22 16:02:29,683 >> tokenizer config file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-150/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2599] 2025-10-22 16:02:29,703 >> Special tokens file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-150/special_tokens_map.json
+[INFO|trainer.py:2810] 2025-10-22 16:02:30,219 >> 
+
+Training completed. Do not forget to share your model on huggingface.co/models =)
+
+
+                                                 {'train_runtime': 38.3946, 'train_samples_per_second': 15.627, 'train_steps_per_second': 3.907, 'train_loss': 0.6288003253936768, 'epoch': 0.01}
+100%|| 150/150 [00:37<00:00,  4.81it/s]100%|| 150/150 [00:37<00:00,  4.01it/s]
+[INFO|trainer.py:4309] 2025-10-22 16:02:30,229 >> Saving model checkpoint to /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints
+[INFO|configuration_utils.py:765] 2025-10-22 16:02:30,323 >> 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 16:02:30,323 >> 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 16:02:30,422 >> 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 16:02:30,426 >> 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 16:02:30,430 >> Special tokens file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/special_tokens_map.json
+***** train metrics *****
+  epoch                    =     0.0123
+  total_flos               =  2243462GF
+  train_loss               =     0.6288
+  train_runtime            = 0:00:38.39
+  train_samples_per_second =     15.627
+  train_steps_per_second   =      3.907
+[INFO|modelcard.py:456] 2025-10-22 16:02:30,648 >> Dropping the following result as it does not have all the necessary fields:
+{'task': {'name': 'Causal Language Modeling', 'type': 'text-generation'}}
+gl064:2368556:2368556 [1] NCCL INFO comm 0x15c0db00 rank 1 nranks 4 cudaDev 1 busId 59000 - Destroy COMPLETE
+gl064:2368555:2368555 [0] NCCL INFO comm 0x14bb0450 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_160152-f7vqjhyf/logs[0m
+
+========================================
+Training completed successfully
+End Time: Wed Oct 22 04:02:32 PM EDT 2025
+========================================
+
+========================================
+STAGE 2: Merging/Exporting Model
+Start Time: Wed Oct 22 04:02:32 PM EDT 2025
+========================================
+Looking for checkpoints in: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints
+Found most recent checkpoint: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-150
+Checkpoint details:
+  Path: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-150
+  Last modified: 2025-10-22 16:02:30.204175325 -0400
+  Training step: 150
+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-150
+
+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-150
+  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 16:02:40,686 >> 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 16:02:40,686 >> 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 16:02:40,686 >> 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 16:02:40,686 >> loading file added_tokens.json from cache at None
+[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:02:40,687 >> loading file special_tokens_map.json from cache at None
+[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:02:40,687 >> 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 16:02:40,687 >> loading file chat_template.jinja from cache at None
+[INFO|tokenization_utils_base.py:2364] 2025-10-22 16:02:40,863 >> 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 16:02:41,054 >> 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 16:02:41,056 >> 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 16:02:41,129 >> 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 16:02:41,129 >> 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 16:02:41,129 >> 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 16:02:41,129 >> loading file added_tokens.json from cache at None
+[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:02:41,129 >> loading file special_tokens_map.json from cache at None
+[INFO|tokenization_utils_base.py:2095] 2025-10-22 16:02:41,129 >> 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 16:02:41,129 >> loading file chat_template.jinja from cache at None
+[INFO|tokenization_utils_base.py:2364] 2025-10-22 16:02:41,298 >> 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 16:02:41,348 >> 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 16:02:41,348 >> 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 16:02:41,348 >> `torch_dtype` is deprecated! Use `dtype` instead!
+[INFO|2025-10-22 16:02:41] llamafactory.model.model_utils.kv_cache:143 >> KV cache is enabled for faster generation.
+[WARNING|logging.py:328] 2025-10-22 16:02:41,741 >> `torch_dtype` is deprecated! Use `dtype` instead!
+[INFO|modeling_utils.py:1172] 2025-10-22 16:02:41,742 >> 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 16:02:41,743 >> Instantiating Qwen2ForCausalLM model under default dtype torch.bfloat16.
+[INFO|configuration_utils.py:986] 2025-10-22 16:02:41,743 >> Generate config GenerationConfig {
+  "bos_token_id": 151643,
+  "eos_token_id": 151643
+}
+
+[INFO|configuration_utils.py:941] 2025-10-22 16:02:41,844 >> 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 16:02:41,844 >> Generate config GenerationConfig {
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048
+}
+
+[INFO|dynamic_module_utils.py:423] 2025-10-22 16:02:41,879 >> Could not locate the custom_generate/generate.py inside Qwen/Qwen2.5-0.5B.
+[INFO|2025-10-22 16:02:41] llamafactory.model.model_utils.attention:143 >> Using torch SDPA for faster training and inference.
+[INFO|2025-10-22 16:02:42] llamafactory.model.adapter:143 >> Merged 1 adapter(s).
+[INFO|2025-10-22 16:02:42] llamafactory.model.adapter:143 >> Loaded adapter(s): /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints/checkpoint-150
+[INFO|2025-10-22 16:02:42] llamafactory.model.loader:143 >> all params: 494,032,768
+[INFO|2025-10-22 16:02:42] llamafactory.train.tuner:143 >> Convert model dtype to: torch.bfloat16.
+[INFO|configuration_utils.py:491] 2025-10-22 16:02:42,967 >> Configuration saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged/config.json
+[INFO|configuration_utils.py:757] 2025-10-22 16:02:42,971 >> Configuration saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged/generation_config.json
+[INFO|modeling_utils.py:4181] 2025-10-22 16:02:44,581 >> Model weights saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged/model.safetensors
+[INFO|tokenization_utils_base.py:2421] 2025-10-22 16:02:44,587 >> 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 16:02:44,591 >> 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 16:02:44,595 >> Special tokens file saved in /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged/special_tokens_map.json
+[INFO|2025-10-22 16:02:44] 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 04:02:45 PM EDT 2025
+========================================
+
+========================================
+Preparing Training Artifacts
+========================================
+Copying configuration files...
+Copying and cleaning training logs...

training_artifacts/merge_config.yaml

@@ -0,0 +1,6 @@
+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-150
+template: default
+export_dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/merged

training_artifacts/train_config.yaml

@@ -0,0 +1,25 @@
+stage: sft
+do_train: true
+max_steps: 150
+do_eval: false
+save_strategy: steps
+save_steps: 50
+logging_steps: 10
+fp16: true
+bf16: false
+overwrite_output_dir: true
+per_device_train_batch_size: 1
+gradient_accumulation_steps: 1
+gradient_checkpointing: true
+model_name_or_path: Qwen/Qwen2.5-0.5B
+finetuning_type: lora
+dataset: my_custom_sft
+dataset_dir: /scratch/zrs2020/LlamaFactoryHelper/LLaMA-Factory/data
+template: default
+cutoff_len: 8096
+val_size: 0.1
+lora_rank: 8
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target: all
+output_dir: /scratch/zrs2020/LlamaFactoryHelper/experiments/lf_torch_test__interactive/checkpoints