0: [2025-08-09 11:42:17,057] [INFO] [axolotl.utils.schemas.validation.check_eval_packing:118] [PID:619259] [RANK:0] explicitly setting `eval_sample_packing` to match `sample_packing`
0: [2025-08-09 11:42:17,057] [INFO] [axolotl.utils.schemas.validation.hint_sample_packing_padding:217] [PID:619259] [RANK:0] Setting `pad_to_sequence_len: true` to prevent memory leaks when sample_packing
3: [2025-08-09 11:42:17,057] [INFO] [axolotl.utils.schemas.validation.check_eval_packing:118] [PID:1158470] [RANK:0] explicitly setting `eval_sample_packing` to match `sample_packing`
2: [2025-08-09 11:42:17,057] [INFO] [axolotl.utils.schemas.validation.check_eval_packing:118] [PID:696294] [RANK:0] explicitly setting `eval_sample_packing` to match `sample_packing`
1: [2025-08-09 11:42:17,057] [INFO] [axolotl.utils.schemas.validation.check_eval_packing:118] [PID:463492] [RANK:0] explicitly setting `eval_sample_packing` to match `sample_packing`
2: [2025-08-09 11:42:17,057] [INFO] [axolotl.utils.schemas.validation.hint_sample_packing_padding:217] [PID:696294] [RANK:0] Setting `pad_to_sequence_len: true` to prevent memory leaks when sample_packing
3: [2025-08-09 11:42:17,057] [INFO] [axolotl.utils.schemas.validation.hint_sample_packing_padding:217] [PID:1158470] [RANK:0] Setting `pad_to_sequence_len: true` to prevent memory leaks when sample_packing
1: [2025-08-09 11:42:17,057] [INFO] [axolotl.utils.schemas.validation.hint_sample_packing_padding:217] [PID:463492] [RANK:0] Setting `pad_to_sequence_len: true` to prevent memory leaks when sample_packing
0: [2025-08-09 11:42:36,408] [INFO] [axolotl.cli.config.load_cfg:244] [PID:619259] [RANK:0] config:
0: {
0:   "activation_offloading": false,
0:   "auto_resume_from_checkpoints": true,
0:   "axolotl_config_path": "/lustre/fswork/projects/rech/dgo/udv55np/train/tmp/1754731818992423200.yaml",
0:   "base_model": "/lustre/fswork/projects/rech/qwv/udv55np/Qwen/Qwen2.5-7B",
0:   "base_model_config": "/lustre/fswork/projects/rech/qwv/udv55np/Qwen/Qwen2.5-7B",
0:   "batch_size": 16,
0:   "bf16": true,
0:   "capabilities": {
0:     "bf16": true,
0:     "compute_capability": "sm_90",
0:     "fp8": false,
0:     "n_gpu": 4,
0:     "n_node": 1
0:   },
0:   "chat_template": "qwen_25",
0:   "dataloader_num_workers": 4,
0:   "dataloader_pin_memory": true,
0:   "dataloader_prefetch_factor": 256,
0:   "dataset_prepared_path": "/lustre/fsn1/projects/rech/dgo/udv55np/dataset/Qwen3-235B-A22B/Qwen2.5-7B/1",
0:   "dataset_processes": 192,
0:   "datasets": [
0:     {
0:       "chat_template": "tokenizer_default",
0:       "data_files": [
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0007.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0009.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0005.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0006.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0014.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0010.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0012.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0008.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0001.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0002.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0013.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0015.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0004.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0011.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0000.jsonl",
0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking/0003.jsonl"
0:       ],
0:       "ds_type": "json",
0:       "field_messages": "conversations",
0:       "message_property_mappings": {
0:         "content": "content",
0:         "role": "role"
0:       },
0:       "path": "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Qwen3-235B-A22B/thinking",
0:       "trust_remote_code": false,
0:       "type": "chat_template"
0:     }
0:   ],
0:   "ddp": true,
0:   "deepspeed": {
0:     "bf16": {
0:       "enabled": true
0:     },
0:     "gradient_accumulation_steps": "auto",
0:     "gradient_clipping": "auto",
0:     "train_batch_size": "auto",
0:     "train_micro_batch_size_per_gpu": "auto",
0:     "wall_clock_breakdown": false,
0:     "zero_optimization": {
0:       "contiguous_gradients": true,
0:       "overlap_comm": true,
0:       "reduce_bucket_size": "auto",
0:       "stage": 3,
0:       "stage3_gather_16bit_weights_on_model_save": true,
0:       "stage3_param_persistence_threshold": "auto",
0:       "stage3_prefetch_bucket_size": "auto",
0:       "sub_group_size": 0
0:     }
0:   },
0:   "device": "cuda:0",
0:   "device_map": {
0:     "": 0
0:   },
0:   "env_capabilities": {
0:     "torch_version": "2.6.0"
0:   },
0:   "eval_batch_size": 1,
0:   "eval_causal_lm_metrics": [
0:     "sacrebleu",
0:     "comet",
0:     "ter",
0:     "chrf"
0:   ],
0:   "eval_max_new_tokens": 128,
0:   "eval_sample_packing": true,
0:   "eval_table_size": 0,
0:   "evals_per_epoch": 0,
0:   "flash_attention": true,
0:   "fp16": false,
0:   "gradient_accumulation_steps": 4,
0:   "gradient_checkpointing": true,
0:   "gradient_checkpointing_kwargs": {
0:     "use_reentrant": true
0:   },
0:   "learning_rate": 5e-06,
0:   "lisa_layers_attribute": "model.layers",
0:   "load_best_model_at_end": false,
0:   "load_in_4bit": false,
0:   "load_in_8bit": false,
0:   "local_rank": 0,
0:   "logging_steps": 10,
0:   "lora_dropout": 0.0,
0:   "loraplus_lr_embedding": 1e-06,
0:   "lr_scheduler": "warmup_stable_decay",
0:   "lr_scheduler_kwargs": {
0:     "min_lr_ratio": 0.1,
0:     "num_decay_steps": 300
0:   },
0:   "max_prompt_len": 512,
0:   "mean_resizing_embeddings": false,
0:   "micro_batch_size": 1,
0:   "model_config_type": "qwen2",
0:   "num_epochs": 1.0,
0:   "optimizer": "adamw_torch_fused",
0:   "output_dir": "/lustre/fswork/projects/rech/dgo/udv55np/ift/Qwen3-235B-A22B/Qwen2.5-7B/1",
0:   "pad_to_sequence_len": true,
0:   "pretrain_multipack_attn": true,
0:   "pretrain_multipack_buffer_size": 10000,
0:   "profiler_steps_start": 0,
0:   "qlora_sharded_model_loading": false,
0:   "ray_num_workers": 1,
0:   "resources_per_worker": {
0:     "GPU": 1
0:   },
0:   "sample_packing": true,
0:   "sample_packing_bin_size": 200,
0:   "sample_packing_group_size": 100000,
0:   "save_only_model": false,
0:   "save_safetensors": true,
0:   "save_steps": 0.2,
0:   "save_total_limit": 20,
0:   "sequence_len": 16384,
0:   "sequence_parallel_degree": 1,
0:   "shuffle_merged_datasets": true,
0:   "skip_prepare_dataset": false,
0:   "special_tokens": {
0:     "bos_token": "<|im_start|>",
0:     "eos_token": "<|im_end|>",
0:     "pad_token": "<|endoftext|>"
0:   },
0:   "strict": false,
0:   "tensor_parallel_size": 1,
0:   "tf32": false,
0:   "tiled_mlp_use_original_mlp": true,
0:   "tokenizer_config": "/lustre/fswork/projects/rech/qwv/udv55np/Qwen/Qwen2.5-7B",
0:   "torch_dtype": "torch.bfloat16",
0:   "train_on_inputs": false,
0:   "trl": {
0:     "log_completions": false,
0:     "mask_truncated_completions": false,
0:     "ref_model_mixup_alpha": 0.9,
0:     "ref_model_sync_steps": 64,
0:     "scale_rewards": true,
0:     "sync_ref_model": false,
0:     "use_vllm": false,
0:     "vllm_server_host": "0.0.0.0",
0:     "vllm_server_port": 8000
0:   },
0:   "use_ray": false,
0:   "use_tensorboard": true,
0:   "val_set_size": 0.0,
0:   "vllm": {
0:     "device": "auto",
0:     "dtype": "auto",
0:     "gpu_memory_utilization": 0.9,
0:     "host": "0.0.0.0",
0:     "port": 8000
0:   },
0:   "warmup_steps": 150,
0:   "weight_decay": 0.0,
0:   "world_size": 4
0: }
0: [2025-08-09 11:42:36,409] [INFO] [axolotl.cli.checks.check_user_token:35] [PID:619259] [RANK:0] Skipping HuggingFace token verification because HF_HUB_OFFLINE is set to True. Only local files will be used.
0: [2025-08-09 11:42:37,286] [INFO] [axolotl.utils.data.shared.load_preprocessed_dataset:471] [PID:619259] [RANK:0] Loading prepared dataset from disk at /lustre/fsn1/projects/rech/dgo/udv55np/dataset/Qwen3-235B-A22B/Qwen2.5-7B/1/5f27dbd9b7ab95f9ee1213e1d97bc04e...
0: [2025-08-09 11:44:37,617] [INFO] [axolotl.utils.samplers.multipack.calc_min_len:435] [PID:619259] [RANK:0] gather_len_batches: [235607, 235607, 235609, 235608]
0: [2025-08-09 11:44:37,640] [INFO] [axolotl.utils.trainer.calc_sample_packing_eff_est:496] [PID:619259] [RANK:0] sample_packing_eff_est across ranks: [0.9936812520027161, 0.9936348795890808, 0.9936854839324951, 0.9936475157737732]
0: [2025-08-09 11:44:37,660] [INFO] [axolotl.utils.data.sft._prepare_standard_dataset:123] [PID:619259] [RANK:0] Maximum number of steps set at 14725
0: You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
2: You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
1: You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
3: You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
3: 
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0: [2025-08-09 11:45:07,275] [INFO] [axolotl.loaders.model._configure_embedding_dtypes:317] [PID:619259] [RANK:0] Converting modules to torch.bfloat16
0: [2025-08-09 11:45:46,402] [INFO] [axolotl.train.save_initial_configs:397] [PID:619259] [RANK:0] Pre-saving tokenizer to /lustre/fswork/projects/rech/dgo/udv55np/ift/Qwen3-235B-A22B/Qwen2.5-7B/1...
0: [2025-08-09 11:45:46,741] [INFO] [axolotl.train.save_initial_configs:400] [PID:619259] [RANK:0] Pre-saving model config to /lustre/fswork/projects/rech/dgo/udv55np/ift/Qwen3-235B-A22B/Qwen2.5-7B/1...
0: [2025-08-09 11:45:46,782] [INFO] [axolotl.train.determine_resume_checkpoint:144] [PID:619259] [RANK:0] Using Auto-resume functionality to start with checkpoint at /lustre/fswork/projects/rech/dgo/udv55np/ift/Qwen3-235B-A22B/Qwen2.5-7B/1/checkpoint-11780
0: [2025-08-09 11:45:46,782] [INFO] [axolotl.train.execute_training:221] [PID:619259] [RANK:0] Starting trainer...
0: [2025-08-09 12:02:34,708] [INFO] [axolotl.utils.samplers.multipack.calc_min_len:435] [PID:619259] [RANK:0] gather_len_batches: [235605, 235605, 235605, 235605]
0: Parameter Offload - Persistent parameters statistics: param_count = 141, numel = 333312
3: Warning: The following arguments do not match the ones in the `trainer_state.json` within the checkpoint directory: 
3: 	save_steps: 0.2 (from args) != 2945 (from trainer_state.json)
0: Warning: The following arguments do not match the ones in the `trainer_state.json` within the checkpoint directory: 
0: 	save_steps: 0.2 (from args) != 2945 (from trainer_state.json)
2: Warning: The following arguments do not match the ones in the `trainer_state.json` within the checkpoint directory: 
2: 	save_steps: 0.2 (from args) != 2945 (from trainer_state.json)
1: Warning: The following arguments do not match the ones in the `trainer_state.json` within the checkpoint directory: 
1: 	save_steps: 0.2 (from args) != 2945 (from trainer_state.json)
0: {'loss': 0.57, 'grad_norm': 0.4802187206078304, 'learning_rate': 5e-06, 'epoch': 0.8}
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0: {'loss': 0.5551, 'grad_norm': 0.5068956524671273, 'learning_rate': 5e-06, 'epoch': 0.82}
0: 
                                                       

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0: {'loss': 0.5755, 'grad_norm': 0.5296194236029464, 'learning_rate': 5e-06, 'epoch': 0.82}
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0: {'loss': 0.5716, 'grad_norm': 0.4869458953925549, 'learning_rate': 5e-06, 'epoch': 0.82}
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0: {'loss': 0.5598, 'grad_norm': 0.4827569806065265, 'learning_rate': 5e-06, 'epoch': 0.83}
0: {'loss': 0.5607, 'grad_norm': 0.4795160016393604, 'learning_rate': 5e-06, 'epoch': 0.83}
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0: {'loss': 0.5699, 'grad_norm': 0.4794376150914544, 'learning_rate': 5e-06, 'epoch': 0.83}
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0: {'loss': 0.5589, 'grad_norm': 0.5027858042146055, 'learning_rate': 5e-06, 'epoch': 0.83}
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0: {'loss': 0.555, 'grad_norm': 0.49198772586208117, 'learning_rate': 5e-06, 'epoch': 0.83}
0: {'loss': 0.5523, 'grad_norm': 0.4671340926810323, 'learning_rate': 5e-06, 'epoch': 0.83}
0:            

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0: {'loss': 0.5668, 'grad_norm': 0.5211037391340804, 'learning_rate': 5e-06, 'epoch': 0.83}
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0: {'loss': 0.5581, 'grad_norm': 0.517465107284683, 'learning_rate': 5e-06, 'epoch': 0.83}
0: s/it]
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0: {'loss': 0.5709, 'grad_norm': 0.4744585122138204, 'learning_rate': 5e-06, 'epoch': 0.83}
0: [1:20:52<6:36:30,  9.71s/it]
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0: {'loss': 0.5535, 'grad_norm': 0.4717598383773368, 'learning_rate': 5e-06, 'epoch': 0.83}
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0: {'loss': 0.5683, 'grad_norm': 0.4720156079396318, 'learning_rate': 5e-06, 'epoch': 0.84}
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0: {'loss': 0.5561, 'grad_norm': 0.4778031494654422, 'learning_rate': 5e-06, 'epoch': 0.84}
0: {'loss': 0.5396, 'grad_norm': 0.44904319192370135, 'learning_rate': 5e-06, 'epoch': 0.84}
0:    

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0: {'loss': 0.5717, 'grad_norm': 0.5156541075745422, 'learning_rate': 5e-06, 'epoch': 0.84}
0: 1:28:08<6:21:02,  9.51s/it]
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0: {'loss': 0.5519, 'grad_norm': 0.48593229900317914, 'learning_rate': 5e-06, 'epoch': 0.84}
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 8
0: {'loss': 0.5614, 'grad_norm': 0.5144130556935973, 'learning_rate': 5e-06, 'epoch': 0.84}
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0: {'loss': 0.5632, 'grad_norm': 0.5068032931467762, 'learning_rate': 5e-06, 'epoch': 0.84}
0: <6:19:31,  9.61s/it]
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0: {'loss': 0.5696, 'grad_norm': 0.4589142692829, 'learning_rate': 5e-06, 'epoch': 0.84}
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0: {'loss': 0.5518, 'grad_norm': 0.4712943093323735, 'learning_rate': 5e-06, 'epoch': 0.85}
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0: {'loss': 0.5608, 'grad_norm': 0.4759879257707382, 'learning_rate': 5e-06, 'epoch': 0.85}
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0: {'loss': 0.5492, 'grad_norm': 0.4637548787023894, 'learning_rate': 5e-06, 'epoch': 0.85}
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0: /it]
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0: {'loss': 0.5579, 'grad_norm': 0.5404043527160066, 'learning_rate': 5e-06, 'epoch': 0.85}
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0: {'loss': 0.5563, 'grad_norm': 0.49299146370782415, 'learning_rate': 5e-06, 'epoch': 0.85}
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0: it]
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0: {'loss': 0.5605, 'grad_norm': 0.5193122833337649, 'learning_rate': 5e-06, 'epoch': 0.86}
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0: {'loss': 0.5728, 'grad_norm': 0.4726915398490453, 'learning_rate': 5e-06, 'epoch': 0.86}
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0: {'loss': 0.5577, 'grad_norm': 0.4419738486330667, 'learning_rate': 5e-06, 'epoch': 0.86}
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0: {'loss': 0.5514, 'grad_norm': 0.5108810230275262, 'learning_rate': 5e-06, 'epoch': 0.86}
0: 14725 [2:29:22<5:22:01,  9.54s/it]
                                                         

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0: {'loss': 0.5516, 'grad_norm': 0.5298401012339898, 'learning_rate': 5e-06, 'epoch': 0.87}
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0: it]
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0: {'loss': 0.556, 'grad_norm': 0.4911787177779066, 'learning_rate': 5e-06, 'epoch': 0.87}
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0: t]
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0: {'loss': 0.5512, 'grad_norm': 0.4594689836796692, 'learning_rate': 5e-06, 'epoch': 0.87}
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0: {'loss': 0.5649, 'grad_norm': 0.48015309070655926, 'learning_rate': 5e-06, 'epoch': 0.88}
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0: {'loss': 0.5532, 'grad_norm': 0.4906333148529489, 'learning_rate': 5e-06, 'epoch': 0.88}
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0: {'loss': 0.5411, 'grad_norm': 0.532845672766041, 'learning_rate': 5e-06, 'epoch': 0.88}
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0: {'loss': 0.5616, 'grad_norm': 0.4667033801536976, 'learning_rate': 5e-06, 'epoch': 0.88}
0: {'loss': 0.5586, 'grad_norm': 0.4720926975114468, 'learning_rate': 5e-06, 'epoch': 0.88}
0:  9.70s/it]
                                                         

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0: {'loss': 0.5433, 'grad_norm': 0.46101281482912465, 'learning_rate': 5e-06, 'epoch': 0.88}
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0: {'loss': 0.5638, 'grad_norm': 0.46711577079108313, 'learning_rate': 5e-06, 'epoch': 0.88}
0: 725 [3:17:18<4:40:18,  9.73s/it]
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0: {'loss': 0.5669, 'grad_norm': 0.462310531733177, 'learning_rate': 5e-06, 'epoch': 0.88}
0: {'loss': 0.5702, 'grad_norm': 0.6012193294614706, 'learning_rate': 5e-06, 'epoch': 0.88}
0: t]
                                                         

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0: {'loss': 0.5468, 'grad_norm': 0.46021958369123916, 'learning_rate': 5e-06, 'epoch': 0.89}
0: 25 [3:24:38<4:30:22,  9.64s/it]
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0: {'loss': 0.5694, 'grad_norm': 0.46048888549805994, 'learning_rate': 5e-06, 'epoch': 0.89}
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0: {'loss': 0.5571, 'grad_norm': 0.4859606873744006, 'learning_rate': 5e-06, 'epoch': 0.89}
0: ]
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0: {'loss': 0.558, 'grad_norm': 0.47074128347201416, 'learning_rate': 5e-06, 'epoch': 0.89}
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0: {'loss': 0.5561, 'grad_norm': 0.465861331129794, 'learning_rate': 5e-06, 'epoch': 0.89}
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0:                                                     

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0: {'loss': 0.5595, 'grad_norm': 0.45328359387338013, 'learning_rate': 5e-06, 'epoch': 0.89}
0: 
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0: {'loss': 0.5616, 'grad_norm': 0.4444998840573777, 'learning_rate': 5e-06, 'epoch': 0.89}
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0: {'loss': 0.558, 'grad_norm': 0.4807190690326318, 'learning_rate': 5e-06, 'epoch': 0.89}
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0: {'loss': 0.5564, 'grad_norm': 0.4738158299875532, 'learning_rate': 5e-06, 'epoch': 0.89}
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0: {'loss': 0.5657, 'grad_norm': 0.4630095805663073, 'learning_rate': 5e-06, 'epoch': 0.9}
0: {'loss': 0.5577, 'grad_norm': 0.48652296446516935, 'learning_rate': 5e-06, 'epoch': 0.9}
0:                                             

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0: {'loss': 0.5536, 'grad_norm': 0.4830007789876022, 'learning_rate': 5e-06, 'epoch': 0.9}
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0: {'loss': 0.5592, 'grad_norm': 0.4719409396910176, 'learning_rate': 5e-06, 'epoch': 0.9}
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0: {'loss': 0.5575, 'grad_norm': 0.5169937099306445, 'learning_rate': 5e-06, 'epoch': 0.9}
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0:                             

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0: {'loss': 0.5576, 'grad_norm': 0.540091702974745, 'learning_rate': 5e-06, 'epoch': 0.91}
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0: {'loss': 0.5503, 'grad_norm': 0.4934629888943367, 'learning_rate': 5e-06, 'epoch': 0.92}
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0:                                              

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0: {'loss': 0.5537, 'grad_norm': 0.4539047542709209, 'learning_rate': 5e-06, 'epoch': 0.93}
0: t]
                                                         

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0: {'loss': 0.5626, 'grad_norm': 0.5094547114710308, 'learning_rate': 5e-06, 'epoch': 0.94}
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0: {'loss': 0.5579, 'grad_norm': 0.47248580507612725, 'learning_rate': 5e-06, 'epoch': 0.95}
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0: ]
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0: {'loss': 0.5568, 'grad_norm': 0.5851253287529448, 'learning_rate': 5e-06, 'epoch': 0.96}
0: {'loss': 0.5526, 'grad_norm': 0.48397491703388273, 'learning_rate': 5e-06, 'epoch': 0.96}
0:                                             

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0: {'loss': 0.562, 'grad_norm': 0.47852595661380687, 'learning_rate': 2.4213131857345744e-06, 'epoch': 0.99}
0: ]
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0: {'loss': 0.5512, 'grad_norm': 0.46584971601918984, 'learning_rate': 1.965712893525916e-06, 'epoch': 0.99}
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0: {'loss': 0.5522, 'grad_norm': 0.4253727898663824, 'learning_rate': 1.749570846833914e-06, 'epoch': 0.99}
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0: {'loss': 0.5538, 'grad_norm': 0.4483976389963377, 'learning_rate': 7.560419467297669e-07, 'epoch': 1.0}
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0:                                                       

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0: {'train_runtime': 28620.7197, 'train_samples_per_second': 8.232, 'train_steps_per_second': 0.514, 'train_loss': 0.11154173983782782, 'epoch': 1.0}
0:                                            

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0: [2025-08-09 20:00:17,981] [INFO] [axolotl.train.save_trained_model:246] [PID:619259] [RANK:0] Training completed! Saving trained model to /lustre/fswork/projects/rech/dgo/udv55np/ift/Qwen3-235B-A22B/Qwen2.5-7B/1.
0: [2025-08-09 20:00:33,353] [INFO] [axolotl.train.save_trained_model:331] [PID:619259] [RANK:0] Model successfully saved to /lustre/fswork/projects/rech/dgo/udv55np/ift/Qwen3-235B-A22B/Qwen2.5-7B/1
2: W0809 20:00:35.777000 696219 torch/distributed/elastic/rendezvous/dynamic_rendezvous.py:1333] The node 'jzxh294.hpc.idris.fr_696219_0' has failed to send a keep-alive heartbeat to the rendezvous '2157844' due to an error of type RendezvousTimeoutError.
3: W0809 20:00:35.795000 1158391 torch/distributed/elastic/rendezvous/dynamic_rendezvous.py:1333] The node 'jzxh305.hpc.idris.fr_1158391_0' has failed to send a keep-alive heartbeat to the rendezvous '2157844' due to an error of type RendezvousTimeoutError.
3: [W809 20:00:35.485150651 TCPStore.cpp:115] [c10d] recvVector failed on SocketImpl(fd=5, addr=[jzxh305]:49614, remote=[jzxh277]:29400): failed to recv, got 0 bytes
3: Exception raised from recvBytes at /pytorch/torch/csrc/distributed/c10d/Utils.hpp:671 (most recent call first):
3: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x14c665ecb1b6 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libc10.so)
3: frame #1: <unknown function> + 0x6311918 (0x14c6a14cf918 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so)
3: frame #2: <unknown function> + 0x6311f39 (0x14c6a14cff39 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so)
3: frame #3: <unknown function> + 0x6314e57 (0x14c6a14d2e57 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so)
3: frame #4: c10d::TCPStore::compareSet(std::string const&, std::vector<unsigned char, std::allocator<unsigned char> > const&, std::vector<unsigned char, std::allocator<unsigned char> > const&) + 0x24c (0x14c6a14cc7bc in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so)
3: frame #5: <unknown function> + 0xe1c9d5 (0x14c6b10c89d5 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libtorch_python.so)
3: frame #6: <unknown function> + 0x51a017 (0x14c6b07c6017 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libtorch_python.so)
3: frame #7: <unknown function> + 0x1ffdc6 (0x5597b002bdc6 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #8: _PyObject_MakeTpCall + 0x25b (0x5597b000c07b in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #9: <unknown function> + 0x22f625 (0x5597b005b625 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #10: _PyEval_EvalFrameDefault + 0x4327 (0x5597b001c4e7 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #11: _PyFunction_Vectorcall + 0x181 (0x5597b003b121 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #12: _PyEval_EvalFrameDefault + 0x4327 (0x5597b001c4e7 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #13: _PyFunction_Vectorcall + 0x181 (0x5597b003b121 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #14: _PyObject_FastCallDictTstate + 0x63 (0x5597b000f853 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #15: _PyObject_Call_Prepend + 0x69 (0x5597b0042e09 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #16: <unknown function> + 0x2e99b9 (0x5597b01159b9 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #17: PyObject_Call + 0x1ed (0x5597b0044ebd in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #18: _PyEval_EvalFrameDefault + 0x4327 (0x5597b001c4e7 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #19: _PyFunction_Vectorcall + 0x181 (0x5597b003b121 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #20: _PyEval_EvalFrameDefault + 0x4327 (0x5597b001c4e7 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #21: <unknown function> + 0x2a4d36 (0x5597b00d0d36 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #22: PyEval_EvalCode + 0x9f (0x5597b00d03ef in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #23: <unknown function> + 0x2c2f2a (0x5597b00eef2a in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #24: <unknown function> + 0x2bf343 (0x5597b00eb343 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #25: <unknown function> + 0x2d4300 (0x5597b0100300 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #26: _PyRun_SimpleFileObject + 0x1ae (0x5597b00ffc5e in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #27: _PyRun_AnyFileObject + 0x44 (0x5597b00ffa44 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #28: Py_RunMain + 0x2df (0x5597b00f9bdf in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #29: Py_BytesMain + 0x37 (0x5597b00bef97 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #30: <unknown function> + 0x29590 (0x14c6b9629590 in /lib64/libc.so.6)
3: frame #31: __libc_start_main + 0x80 (0x14c6b9629640 in /lib64/libc.so.6)
3: frame #32: <unknown function> + 0x292e3d (0x5597b00bee3d in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: 
3: W0809 20:00:36.953000 1158391 torch/distributed/elastic/rendezvous/dynamic_rendezvous.py:1284] The node 'jzxh305.hpc.idris.fr_1158391_0' has failed to shutdown the rendezvous '2157844' due to an error of type RendezvousConnectionError.
3: [W809 20:00:36.500066626 TCPStore.cpp:106] [c10d] sendBytes failed on SocketImpl(fd=5, addr=[jzxh305]:49614, remote=[jzxh277]:29400): Broken pipe
3: Exception raised from sendBytes at /pytorch/torch/csrc/distributed/c10d/Utils.hpp:646 (most recent call first):
3: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x14c665ecb1b6 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libc10.so)
3: frame #1: <unknown function> + 0x6311c1d (0x14c6a14cfc1d in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so)
3: frame #2: <unknown function> + 0x63146ac (0x14c6a14d26ac in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so)
3: frame #3: <unknown function> + 0x631484d (0x14c6a14d284d in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so)
3: frame #4: c10d::TCPStore::compareSet(std::string const&, std::vector<unsigned char, std::allocator<unsigned char> > const&, std::vector<unsigned char, std::allocator<unsigned char> > const&) + 0x310 (0x14c6a14cc880 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so)
3: frame #5: <unknown function> + 0xe1c9d5 (0x14c6b10c89d5 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libtorch_python.so)
3: frame #6: <unknown function> + 0x51a017 (0x14c6b07c6017 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/lib/python3.11/site-packages/torch/lib/libtorch_python.so)
3: frame #7: <unknown function> + 0x1ffdc6 (0x5597b002bdc6 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #8: _PyObject_MakeTpCall + 0x25b (0x5597b000c07b in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #9: <unknown function> + 0x22f625 (0x5597b005b625 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #10: _PyEval_EvalFrameDefault + 0x4327 (0x5597b001c4e7 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #11: _PyFunction_Vectorcall + 0x181 (0x5597b003b121 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #12: _PyObject_FastCallDictTstate + 0x63 (0x5597b000f853 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #13: _PyObject_Call_Prepend + 0x69 (0x5597b0042e09 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #14: <unknown function> + 0x2e99b9 (0x5597b01159b9 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #15: PyObject_Call + 0x1ed (0x5597b0044ebd in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #16: _PyEval_EvalFrameDefault + 0x4327 (0x5597b001c4e7 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #17: _PyFunction_Vectorcall + 0x181 (0x5597b003b121 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #18: _PyEval_EvalFrameDefault + 0x4327 (0x5597b001c4e7 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #19: <unknown function> + 0x2a4d36 (0x5597b00d0d36 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #20: PyEval_EvalCode + 0x9f (0x5597b00d03ef in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #21: <unknown function> + 0x2c2f2a (0x5597b00eef2a in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #22: <unknown function> + 0x2bf343 (0x5597b00eb343 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #23: <unknown function> + 0x2d4300 (0x5597b0100300 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #24: _PyRun_SimpleFileObject + 0x1ae (0x5597b00ffc5e in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #25: _PyRun_AnyFileObject + 0x44 (0x5597b00ffa44 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #26: Py_RunMain + 0x2df (0x5597b00f9bdf in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #27: Py_BytesMain + 0x37 (0x5597b00bef97 in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: frame #28: <unknown function> + 0x29590 (0x14c6b9629590 in /lib64/libc.so.6)
3: frame #29: __libc_start_main + 0x80 (0x14c6b9629640 in /lib64/libc.so.6)
3: frame #30: <unknown function> + 0x292e3d (0x5597b00bee3d in /lustre/fswork/projects/rech/qwv/udv55np/axolotl/bin/python)
3: 
3: W0809 20:00:36.958000 1158391 torch/distributed/elastic/rendezvous/dynamic_rendezvous.py:1284] The node 'jzxh305.hpc.idris.fr_1158391_0' has failed to shutdown the rendezvous '2157844' due to an error of type RendezvousConnectionError.