| === Thu Mar 19 19:06:45 UTC 2026 Starting training run === |
| Config: load_in_8bit + device_map auto |
| Model cache: symlinked to hub path |
| [19:06:45] Verifying model cache... |
| [19:06:45] Model shards found: 11 |
| [19:06:45] Phase 4: Smoke test (10 steps) |
| [19:06:45] NOTE: Dataset tokenization may take 15-20 min. |
|
|
| #@@ #@@ @@# @@# |
| @@ @@ @@ @@ =@@# @@ #@ =@@#. |
| @@ #@@@@@@@@@ @@ #@#@= @@ #@ .=@@ |
| #@@@@@@@@@@@@@@@@@ =@# @# ##= ## =####=+ @@ =#####+ =#@@###. @@ |
| @@@@@@@@@@/ +@@/ +@@ #@ =@= #@= @@ =@#+ +#@# @@ =@#+ +#@# #@. @@ |
| @@@@@@@@@@ ##@@ ##@@ =@# @# =@# @# @@ @@ @@ @@ #@ #@ @@ |
| @@@@@@@@@@@@@@@@@@@@ #@=+++#@= =@@# @@ @@ @@ @@ #@ #@ @@ |
| =@#=====@@ =@# @# @@ @@ @@ @@ #@ #@ @@ |
| @@@@@@@@@@@@@@@@ @@@@ #@ #@= #@= +@@ #@# =@# @@. =@# =@# #@. @@ |
| =@# @# #@= #@ =#@@@@#= +#@@= +#@@@@#= .##@@+ @@ |
| @@@@ @@@@@@@@@@@@@@@@ |
|
|
| The following values were not passed to `accelerate launch` and had defaults used instead: |
| `--num_processes` was set to a value of `1` |
| `--num_machines` was set to a value of `1` |
| `--mixed_precision` was set to a value of `'no'` |
| `--dynamo_backend` was set to a value of `'no'` |
| To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`. |
| [2026-03-19 19:07:03,554] [INFO] [axolotl.cli.config] config: |
| { |
| "activation_offloading": false, |
| "adapter": "lora", |
| "axolotl_config_path": "/workspace/training/axolotl_config_blackwell.yaml", |
| "base_model": "Qwen/Qwen3.5-27B", |
| "base_model_config": "Qwen/Qwen3.5-27B", |
| "batch_size": 8, |
| "bf16": true, |
| "capabilities": { |
| "bf16": true, |
| "compute_capability": "sm_120", |
| "fp8": true, |
| "n_gpu": 1, |
| "n_node": 1, |
| "tf32": true |
| }, |
| "context_parallel_size": 1, |
| "dataloader_num_workers": 1, |
| "dataloader_pin_memory": true, |
| "dataloader_prefetch_factor": 256, |
| "dataset_num_proc": 16, |
| "datasets": [ |
| { |
| "chat_template": "tokenizer_default", |
| "field_messages": "messages", |
| "message_property_mappings": { |
| "content": "content", |
| "role": "role" |
| }, |
| "path": "train_messages.jsonl", |
| "roles_to_train": [ |
| "assistant" |
| ], |
| "trust_remote_code": false, |
| "type": "chat_template" |
| } |
| ], |
| "ddp": false, |
| "device": "cuda:0", |
| "dion_rank_fraction": 1.0, |
| "dion_rank_multiple_of": 1, |
| "eaft_alpha": 1.0, |
| "eaft_k": 20, |
| "env_capabilities": { |
| "torch_version": "2.10.0" |
| }, |
| "eval_batch_size": 1, |
| "eval_causal_lm_metrics": [ |
| "sacrebleu", |
| "comet", |
| "ter", |
| "chrf" |
| ], |
| "eval_max_new_tokens": 128, |
| "eval_steps": 50, |
| "eval_strategy": "steps", |
| "eval_table_size": 0, |
| "experimental_skip_move_to_device": true, |
| "flash_attention": false, |
| "fp16": false, |
| "generate_samples": false, |
| "generation_do_sample": true, |
| "generation_max_new_tokens": 50, |
| "generation_prompt_ratio": 0.5, |
| "generation_temperature": 0.7, |
| "gradient_accumulation_steps": 8, |
| "gradient_checkpointing": true, |
| "gradient_checkpointing_kwargs": { |
| "use_reentrant": false |
| }, |
| "greater_is_better": false, |
| "include_tkps": true, |
| "is_multimodal": true, |
| "learning_rate": 0.0002, |
| "lisa_layers_attribute": "model.layers", |
| "load_best_model_at_end": true, |
| "load_in_4bit": false, |
| "load_in_8bit": true, |
| "local_rank": 0, |
| "logging_steps": 5, |
| "lora_alpha": 64, |
| "lora_dropout": 0.05, |
| "lora_r": 32, |
| "lora_target_modules": [ |
| "q_proj", |
| "k_proj", |
| "v_proj", |
| "o_proj", |
| "gate_proj", |
| "down_proj", |
| "up_proj" |
| ], |
| "loraplus_lr_embedding": 1e-06, |
| "lr_scheduler": "cosine", |
| "max_grad_norm": 1.0, |
| "max_steps": 10, |
| "mean_resizing_embeddings": false, |
| "metric_for_best_model": "eval_loss", |
| "micro_batch_size": 1, |
| "model_config_type": "qwen3_5", |
| "model_config_type_text": "qwen3_5_text", |
| "num_epochs": 2.0, |
| "num_generation_samples": 3, |
| "optimizer": "adamw_torch", |
| "otel_metrics_host": "localhost", |
| "otel_metrics_port": 8000, |
| "output_dir": "./output/qwen3.5-27b-indian-legal", |
| "pad_to_sequence_len": true, |
| "pretrain_multipack_attn": true, |
| "processor_config": "Qwen/Qwen3.5-27B", |
| "profiler_steps_start": 0, |
| "qlora_sharded_model_loading": false, |
| "quantize_moe_experts": false, |
| "ray_num_workers": 1, |
| "resources_per_worker": { |
| "GPU": 1 |
| }, |
| "sample_packing": false, |
| "sample_packing_bin_size": 200, |
| "sample_packing_group_size": 100000, |
| "save_only_model": false, |
| "save_safetensors": true, |
| "save_steps": 25, |
| "save_strategy": "steps", |
| "save_total_limit": 5, |
| "sequence_len": 4096, |
| "shuffle_before_merging_datasets": false, |
| "shuffle_merged_datasets": true, |
| "skip_prepare_dataset": false, |
| "special_tokens": { |
| "eos_token": "<|im_end|>" |
| }, |
| "streaming_multipack_buffer_size": 10000, |
| "strict": false, |
| "tensor_parallel_size": 1, |
| "test_datasets": [ |
| { |
| "chat_template": "tokenizer_default", |
| "field_messages": "messages", |
| "message_property_mappings": { |
| "content": "content", |
| "role": "role" |
| }, |
| "path": "val_messages.jsonl", |
| "trust_remote_code": false, |
| "type": "chat_template" |
| } |
| ], |
| "tf32": true, |
| "tiled_mlp_use_original_mlp": true, |
| "tokenizer_config": "Qwen/Qwen3.5-27B", |
| "tokenizer_save_jinja_files": true, |
| "torch_dtype": "torch.bfloat16", |
| "train_on_inputs": false, |
| "trl": { |
| "async_prefetch": false, |
| "log_completions": false, |
| "mask_truncated_completions": false, |
| "ref_model_mixup_alpha": 0.9, |
| "ref_model_sync_steps": 64, |
| "replay_buffer_size": 0, |
| "replay_recompute_logps": true, |
| "reroll_max_groups": 1, |
| "reroll_start_fraction": 1.0, |
| "reward_num_workers": 1, |
| "scale_rewards": true, |
| "skip_zero_advantage_batches": true, |
| "sync_ref_model": false, |
| "use_data_producer": false, |
| "use_vllm": false, |
| "vllm_lora_sync": false, |
| "vllm_server_host": "0.0.0.0", |
| "vllm_server_port": 8000 |
| }, |
| "use_otel_metrics": false, |
| "use_ray": false, |
| "val_set_size": 0.0, |
| "vllm": { |
| "device": "auto", |
| "dtype": "auto", |
| "gpu_memory_utilization": 0.9, |
| "host": "0.0.0.0", |
| "port": 8000 |
| }, |
| "warmup_ratio": 0.05, |
| "weight_decay": 0.01, |
| "world_size": 1 |
| } |
| [2026-03-19 19:07:05,417] [INFO] [axolotl.utils.data.shared] Unable to find prepared dataset in last_run_prepared/015733b0bc51bbfc77a3f2273afd718b |
| [2026-03-19 19:07:05,417] [INFO] [axolotl.utils.data.sft] Loading raw datasets... |
| [2026-03-19 19:07:05,417] [WARNING] [axolotl.utils.data.sft] Processing datasets during training can lead to VRAM instability. Please pre-process your dataset using `axolotl preprocess path/to/config.yml`. |
| [2026-03-19 19:07:05,780] [INFO] [axolotl.utils.data.wrappers] Loading dataset: train_messages.jsonl with base_type: chat_template and prompt_style: None |
| [2026-03-19 19:07:05,785] [INFO] [axolotl.prompt_strategies.chat_template] Using chat template: |
| --- |
| {%- set image_count = namespace(value=0) %} |
| {%- set video_count = namespace(value=0) %} |
| {%- macro render_content(content, do_vision_count, is_system_content=false) %} |
| {%- if content is string %} |
| {{- content }} |
| {%- elif content is iterable and content is not mapping %} |
| {%- for item in content %} |
| {%- if 'image' in item or 'image_url' in item or item.type == 'image' %} |
| {%- if is_system_content %} |
| {{- raise_exception('System message cannot contain images.') }} |
| {%- endif %} |
| {%- if do_vision_count %} |
| {%- set image_count.value = image_count.value + 1 %} |
| {%- endif %} |
| {%- if add_vision_id %} |
| {{- 'Picture ' ~ image_count.value ~ ': ' }} |
| {%- endif %} |
| {{- '<|vision_start|><|image_pad|><|vision_end|>' }} |
| {%- elif 'video' in item or item.type == 'video' %} |
| {%- if is_system_content %} |
| {{- raise_exception('System message cannot contain videos.') }} |
| {%- endif %} |
| {%- if do_vision_count %} |
| {%- set video_count.value = video_count.value + 1 %} |
| {%- endif %} |
| {%- if add_vision_id %} |
| {{- 'Video ' ~ video_count.value ~ ': ' }} |
| {%- endif %} |
| {{- '<|vision_start|><|video_pad|><|vision_end|>' }} |
| {%- elif 'text' in item %} |
| {{- item.text }} |
| {%- else %} |
| {{- raise_exception('Unexpected item type in content.') }} |
| {%- endif %} |
| {%- endfor %} |
| {%- elif content is none or content is undefined %} |
| {{- '' }} |
| {%- else %} |
| {{- raise_exception('Unexpected content type.') }} |
| {%- endif %} |
| {%- endmacro %} |
| {%- if not messages %} |
| {{- raise_exception('No messages provided.') }} |
| {%- endif %} |
| {%- if tools and tools is iterable and tools is not mapping %} |
| {{- '<|im_start|>system\n' }} |
| {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }} |
| {%- for tool in tools %} |
| {{- "\n" }} |
| {{- tool | tojson }} |
| {%- endfor %} |
| {{- "\n</tools>" }} |
| {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }} |
| {%- if messages[0].role == 'system' %} |
| {%- set content = render_content(messages[0].content, false, true)|trim %} |
| {%- if content %} |
| {{- '\n\n' + content }} |
| {%- endif %} |
| {%- endif %} |
| {{- '<|im_end|>\n' }} |
| {%- else %} |
| {%- if messages[0].role == 'system' %} |
| {%- set content = render_content(messages[0].content, false, true)|trim %} |
| {{- '<|im_start|>system\n' + content + '<|im_end|>\n' }} |
| {%- endif %} |
| {%- endif %} |
| {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %} |
| {%- for message in messages[::-1] %} |
| {%- set index = (messages|length - 1) - loop.index0 %} |
| {%- if ns.multi_step_tool and message.role == "user" %} |
| {%- set content = render_content(message.content, false)|trim %} |
| {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %} |
| {%- set ns.multi_step_tool = false %} |
| {%- set ns.last_query_index = index %} |
| {%- endif %} |
| {%- endif %} |
| {%- endfor %} |
| {%- if ns.multi_step_tool %} |
| {{- raise_exception('No user query found in messages.') }} |
| {%- endif %} |
| {%- for message in messages %} |
| {%- set content = render_content(message.content, true)|trim %} |
| {%- if message.role == "system" %} |
| {%- if not loop.first %} |
| {{- raise_exception('System message must be at the beginning.') }} |
| {%- endif %} |
| {%- elif message.role == "user" %} |
| {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }} |
| {%- elif message.role == "assistant" %} |
| {%- set reasoning_content = '' %} |
| {%- if message.reasoning_content is string %} |
| {%- set reasoning_content = message.reasoning_content %} |
| {%- else %} |
| {%- if '</think>' in content %} |
| {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %} |
| {%- set content = content.split('</think>')[-1].lstrip('\n') %} |
| {%- endif %} |
| {%- endif %} |
| {%- set reasoning_content = reasoning_content|trim %} |
| {%- if loop.index0 > ns.last_query_index %} |
| {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }} |
| {%- else %} |
| {{- '<|im_start|>' + message.role + '\n' + content }} |
| {%- endif %} |
| {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %} |
| {%- for tool_call in message.tool_calls %} |
| {%- if tool_call.function is defined %} |
| {%- set tool_call = tool_call.function %} |
| {%- endif %} |
| {%- if loop.first %} |
| {%- if content|trim %} |
| {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }} |
| {%- else %} |
| {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }} |
| {%- endif %} |
| {%- else %} |
| {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }} |
| {%- endif %} |
| {%- if tool_call.arguments is defined %} |
| {%- for args_name, args_value in tool_call.arguments|items %} |
| {{- '<parameter=' + args_name + '>\n' }} |
| {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %} |
| {{- args_value }} |
| {{- '\n</parameter>\n' }} |
| {%- endfor %} |
| {%- endif %} |
| {{- '</function>\n</tool_call>' }} |
| {%- endfor %} |
| {%- endif %} |
| {{- '<|im_end|>\n' }} |
| {%- elif message.role == "tool" %} |
| {%- if loop.previtem and loop.previtem.role != "tool" %} |
| {{- '<|im_start|>user' }} |
| {%- endif %} |
| {{- '\n<tool_response>\n' }} |
| {{- content }} |
| {{- '\n</tool_response>' }} |
| {%- if not loop.last and loop.nextitem.role != "tool" %} |
| {{- '<|im_end|>\n' }} |
| {%- elif loop.last %} |
| {{- '<|im_end|>\n' }} |
| {%- endif %} |
| {%- else %} |
| {{- raise_exception('Unexpected message role.') }} |
| {%- endif %} |
| {%- endfor %} |
| {%- if add_generation_prompt %} |
| {{- '<|im_start|>assistant\n' }} |
| {%- if enable_thinking is defined and enable_thinking is false %} |
| {{- '<think>\n\n</think>\n\n' }} |
| {%- else %} |
| {{- '<think>\n' }} |
| {%- endif %} |
| {%- endif %} |
| --- |
| [2026-03-19 19:07:06,062] [INFO] [axolotl.utils.data.utils] min_input_len: 493 |
| [2026-03-19 19:07:06,062] [INFO] [axolotl.utils.data.utils] max_input_len: 4030 |
|
Dropping Invalid Sequences (<None or >4096) (num_proc=16): 0%| | 0/20219 [00:00<?, ? examples/s]
Dropping Invalid Sequences (<None or >4096) (num_proc=16): 5%|▍ | 1000/20219 [00:00<00:08, 2391.11 examples/s]
Dropping Invalid Sequences (<None or >4096) (num_proc=16): 69%|██████▉ | 13902/20219 [00:00<00:00, 33740.24 examples/s]
Dropping Invalid Sequences (<None or >4096) (num_proc=16): 100%|██████████| 20219/20219 [00:00<00:00, 28069.01 examples/s] |
|
Saving the dataset (0/16 shards): 0%| | 0/20219 [00:00<?, ? examples/s]
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Saving the dataset (14/16 shards): 97%|█████████▋| 19692/20219 [00:00<00:00, 2602.42 examples/s]
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Saving the dataset (16/16 shards): 100%|██████████| 20219/20219 [00:00<00:00, 36369.80 examples/s] |
| [2026-03-19 19:07:07,410] [INFO] [axolotl.utils.data.shared] Unable to find prepared dataset in last_run_prepared/a8897a7fc14fd1d875ca8677fc9b5dda |
| [2026-03-19 19:07:07,410] [INFO] [axolotl.utils.data.sft] Loading raw datasets... |
| [2026-03-19 19:07:07,410] [WARNING] [axolotl.utils.data.sft] Processing datasets during training can lead to VRAM instability. Please pre-process your dataset using `axolotl preprocess path/to/config.yml`. |
| [2026-03-19 19:07:07,531] [INFO] [axolotl.utils.data.wrappers] Loading dataset: val_messages.jsonl with base_type: chat_template and prompt_style: None |
| [2026-03-19 19:07:07,532] [INFO] [axolotl.prompt_strategies.chat_template] Using chat template: |
| --- |
| {%- set image_count = namespace(value=0) %} |
| {%- set video_count = namespace(value=0) %} |
| {%- macro render_content(content, do_vision_count, is_system_content=false) %} |
| {%- if content is string %} |
| {{- content }} |
| {%- elif content is iterable and content is not mapping %} |
| {%- for item in content %} |
| {%- if 'image' in item or 'image_url' in item or item.type == 'image' %} |
| {%- if is_system_content %} |
| {{- raise_exception('System message cannot contain images.') }} |
| {%- endif %} |
| {%- if do_vision_count %} |
| {%- set image_count.value = image_count.value + 1 %} |
| {%- endif %} |
| {%- if add_vision_id %} |
| {{- 'Picture ' ~ image_count.value ~ ': ' }} |
| {%- endif %} |
| {{- '<|vision_start|><|image_pad|><|vision_end|>' }} |
| {%- elif 'video' in item or item.type == 'video' %} |
| {%- if is_system_content %} |
| {{- raise_exception('System message cannot contain videos.') }} |
| {%- endif %} |
| {%- if do_vision_count %} |
| {%- set video_count.value = video_count.value + 1 %} |
| {%- endif %} |
| {%- if add_vision_id %} |
| {{- 'Video ' ~ video_count.value ~ ': ' }} |
| {%- endif %} |
| {{- '<|vision_start|><|video_pad|><|vision_end|>' }} |
| {%- elif 'text' in item %} |
| {{- item.text }} |
| {%- else %} |
| {{- raise_exception('Unexpected item type in content.') }} |
| {%- endif %} |
| {%- endfor %} |
| {%- elif content is none or content is undefined %} |
| {{- '' }} |
| {%- else %} |
| {{- raise_exception('Unexpected content type.') }} |
| {%- endif %} |
| {%- endmacro %} |
| {%- if not messages %} |
| {{- raise_exception('No messages provided.') }} |
| {%- endif %} |
| {%- if tools and tools is iterable and tools is not mapping %} |
| {{- '<|im_start|>system\n' }} |
| {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }} |
| {%- for tool in tools %} |
| {{- "\n" }} |
| {{- tool | tojson }} |
| {%- endfor %} |
| {{- "\n</tools>" }} |
| {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }} |
| {%- if messages[0].role == 'system' %} |
| {%- set content = render_content(messages[0].content, false, true)|trim %} |
| {%- if content %} |
| {{- '\n\n' + content }} |
| {%- endif %} |
| {%- endif %} |
| {{- '<|im_end|>\n' }} |
| {%- else %} |
| {%- if messages[0].role == 'system' %} |
| {%- set content = render_content(messages[0].content, false, true)|trim %} |
| {{- '<|im_start|>system\n' + content + '<|im_end|>\n' }} |
| {%- endif %} |
| {%- endif %} |
| {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %} |
| {%- for message in messages[::-1] %} |
| {%- set index = (messages|length - 1) - loop.index0 %} |
| {%- if ns.multi_step_tool and message.role == "user" %} |
| {%- set content = render_content(message.content, false)|trim %} |
| {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %} |
| {%- set ns.multi_step_tool = false %} |
| {%- set ns.last_query_index = index %} |
| {%- endif %} |
| {%- endif %} |
| {%- endfor %} |
| {%- if ns.multi_step_tool %} |
| {{- raise_exception('No user query found in messages.') }} |
| {%- endif %} |
| {%- for message in messages %} |
| {%- set content = render_content(message.content, true)|trim %} |
| {%- if message.role == "system" %} |
| {%- if not loop.first %} |
| {{- raise_exception('System message must be at the beginning.') }} |
| {%- endif %} |
| {%- elif message.role == "user" %} |
| {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }} |
| {%- elif message.role == "assistant" %} |
| {%- set reasoning_content = '' %} |
| {%- if message.reasoning_content is string %} |
| {%- set reasoning_content = message.reasoning_content %} |
| {%- else %} |
| {%- if '</think>' in content %} |
| {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %} |
| {%- set content = content.split('</think>')[-1].lstrip('\n') %} |
| {%- endif %} |
| {%- endif %} |
| {%- set reasoning_content = reasoning_content|trim %} |
| {%- if loop.index0 > ns.last_query_index %} |
| {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }} |
| {%- else %} |
| {{- '<|im_start|>' + message.role + '\n' + content }} |
| {%- endif %} |
| {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %} |
| {%- for tool_call in message.tool_calls %} |
| {%- if tool_call.function is defined %} |
| {%- set tool_call = tool_call.function %} |
| {%- endif %} |
| {%- if loop.first %} |
| {%- if content|trim %} |
| {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }} |
| {%- else %} |
| {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }} |
| {%- endif %} |
| {%- else %} |
| {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }} |
| {%- endif %} |
| {%- if tool_call.arguments is defined %} |
| {%- for args_name, args_value in tool_call.arguments|items %} |
| {{- '<parameter=' + args_name + '>\n' }} |
| {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %} |
| {{- args_value }} |
| {{- '\n</parameter>\n' }} |
| {%- endfor %} |
| {%- endif %} |
| {{- '</function>\n</tool_call>' }} |
| {%- endfor %} |
| {%- endif %} |
| {{- '<|im_end|>\n' }} |
| {%- elif message.role == "tool" %} |
| {%- if loop.previtem and loop.previtem.role != "tool" %} |
| {{- '<|im_start|>user' }} |
| {%- endif %} |
| {{- '\n<tool_response>\n' }} |
| {{- content }} |
| {{- '\n</tool_response>' }} |
| {%- if not loop.last and loop.nextitem.role != "tool" %} |
| {{- '<|im_end|>\n' }} |
| {%- elif loop.last %} |
| {{- '<|im_end|>\n' }} |
| {%- endif %} |
| {%- else %} |
| {{- raise_exception('Unexpected message role.') }} |
| {%- endif %} |
| {%- endfor %} |
| {%- if add_generation_prompt %} |
| {{- '<|im_start|>assistant\n' }} |
| {%- if enable_thinking is defined and enable_thinking is false %} |
| {{- '<think>\n\n</think>\n\n' }} |
| {%- else %} |
| {{- '<think>\n' }} |
| {%- endif %} |
| {%- endif %} |
| --- |
| [2026-03-19 19:07:07,724] [INFO] [axolotl.utils.data.utils] min_input_len: 494 |
| [2026-03-19 19:07:07,724] [INFO] [axolotl.utils.data.utils] max_input_len: 3493 |
|
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|
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| [2026-03-19 19:07:08,624] [INFO] [axolotl.utils.data.sft] Maximum number of steps set at 10 |
| The fast path is not available because one of the required library is not installed. Falling back to torch implementation. To install follow https: |
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| [2026-03-19 19:08:16,715] [INFO] [axolotl.loaders.model] converting PEFT model w/ prepare_model_for_kbit_training |
| [2026-03-19 19:08:16,728] [INFO] [axolotl.loaders.model] Converting modules to torch.bfloat16 |
| trainable params: 159,383,552 || all params: 27,516,112,112 || trainable%: 0.5792 |
| [2026-03-19 19:08:22,210] [INFO] [axolotl.train] Pre-saving adapter config to ./output/qwen3.5-27b-indian-legal... |
| [2026-03-19 19:08:22,211] [INFO] [axolotl.train] Pre-saving tokenizer to ./output/qwen3.5-27b-indian-legal... |
| [2026-03-19 19:08:22,516] [INFO] [axolotl.train] Pre-saving model config to ./output/qwen3.5-27b-indian-legal... |
| [2026-03-19 19:08:22,524] [INFO] [axolotl.train] Pre-saving processor to ./output/qwen3.5-27b-indian-legal... |
| [2026-03-19 19:08:23,355] [INFO] [axolotl.train] Starting trainer... |
| 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: {'eos_token_id': 248046, 'bos_token_id': None, 'pad_token_id': 248044}. |
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|
{'eval_loss': '1.931', 'eval_runtime': '1846', 'eval_samples_per_second': '0.579', 'eval_steps_per_second': '0.579', 'eval_ppl': '6.899', 'memory/max_active (GiB)': '38.29', 'memory/max_allocated (GiB)': '38.29', 'memory/device_reserved (GiB)': '38.84', 'epoch': 0} |
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{'loss': '1.815', 'grad_norm': '0.06905', 'learning_rate': '0.0001309', 'ppl': '6.138', 'memory/max_active (GiB)': '61.44', 'memory/max_allocated (GiB)': '61.44', 'memory/device_reserved (GiB)': '65.71', 'tokens/train_per_sec_per_gpu': '2.494', 'tokens/total': 163840, 'tokens/trainable': 15062, 'epoch': '0.001978'} |
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{'loss': '1.518', 'grad_norm': '0.083', 'learning_rate': '4.894e-06', 'ppl': '4.561', 'memory/max_active (GiB)': '61.51', 'memory/max_allocated (GiB)': '61.51', 'memory/device_reserved (GiB)': '66.04', 'tokens/train_per_sec_per_gpu': '20.06', 'tokens/total': 327680, 'tokens/trainable': 34140, 'epoch': '0.003957'} |
|
100%|██████████| 10/10 [45:07<00:00, 108.84s/it][2026-03-19 19:53:30,947] [INFO] [axolotl.core.trainers.base] Saving model checkpoint to ./output/qwen3.5-27b-indian-legal/checkpoint-10 |
|
{'train_runtime': '2709', 'train_samples_per_second': '0.03', 'train_steps_per_second': '0.004', 'train_loss': '1.666', 'memory/max_active (GiB)': '29.68', 'memory/max_allocated (GiB)': '29.68', 'memory/device_reserved (GiB)': '66.04', 'epoch': '0.003957', 'tokens/train_per_sec_per_gpu': '0'} |
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| [2026-03-19 19:53:33,288] [INFO] [axolotl.train] Training completed! Saving trained model to ./output/qwen3.5-27b-indian-legal. |
| [2026-03-19 19:53:34,152] [INFO] [axolotl.train] Model successfully saved to ./output/qwen3.5-27b-indian-legal |
| [19:53:40] Smoke test exit: 0 |
| [19:53:41] Smoke test PASSED |
| |
