| === STDOUT === |
| [2025-12-03 19:59:19,939] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) |
| [2025-12-03 19:59:20,529] [INFO] [root.spawn:60] [PID:121] gcc -pthread -B /root/miniconda3/envs/py3.11/compiler_compat -DNDEBUG -fwrapv -O2 -Wall -fPIC -O2 -isystem /root/miniconda3/envs/py3.11/include -fPIC -O2 -isystem /root/miniconda3/envs/py3.11/include -fPIC -c /tmp/tmpp0n1fqw2/test.c -o /tmp/tmpp0n1fqw2/test.o |
| [2025-12-03 19:59:20,571] [INFO] [root.spawn:60] [PID:121] gcc -pthread -B /root/miniconda3/envs/py3.11/compiler_compat /tmp/tmpp0n1fqw2/test.o -laio -o /tmp/tmpp0n1fqw2/a.out |
| [WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH |
| [WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3 |
| [WARNING] using untested triton version (2.3.1), only 1.0.0 is known to be compatible |
| [33m[2025-12-03 19:59:22,343] [WARNING] [axolotl.utils.config.models.input.hint_lora_8bit:1221] [PID:121] [RANK:0] We recommend setting `load_in_8bit: true` for LORA finetuning[39m |
| [2025-12-03 19:59:22,344] [DEBUG] [axolotl.normalize_config:83] [PID:121] [RANK:0] bf16 support detected, enabling for this configuration.[39m |
| [2025-12-03 19:59:22,897] [INFO] [axolotl.normalize_config:207] [PID:121] [RANK:0] GPU memory usage baseline: 0.000GB (+0.471GB misc)[39m |
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| [2025-12-03 19:59:26,240] [DEBUG] [axolotl.load_tokenizer:293] [PID:121] [RANK:0] EOS: 0 / <|endoftext|>[39m |
| [2025-12-03 19:59:26,240] [DEBUG] [axolotl.load_tokenizer:294] [PID:121] [RANK:0] BOS: 0 / <|endoftext|>[39m |
| [2025-12-03 19:59:26,240] [DEBUG] [axolotl.load_tokenizer:295] [PID:121] [RANK:0] PAD: 0 / <|endoftext|>[39m |
| [2025-12-03 19:59:26,240] [DEBUG] [axolotl.load_tokenizer:296] [PID:121] [RANK:0] UNK: 0 / <|endoftext|>[39m |
| [2025-12-03 19:59:26,240] [INFO] [axolotl.load_tokenizer:310] [PID:121] [RANK:0] No Chat template selected. Consider adding a chat template for easier inference.[39m |
| [2025-12-03 19:59:26,241] [INFO] [axolotl.load_tokenized_prepared_datasets:234] [PID:121] [RANK:0] Unable to find prepared dataset in last_run_prepared/c8b534ced2ddf0659aff669f20b527cd[39m |
| [2025-12-03 19:59:26,241] [INFO] [axolotl.load_tokenized_prepared_datasets:235] [PID:121] [RANK:0] Loading raw datasets...[39m |
| [33m[2025-12-03 19:59:26,241] [WARNING] [axolotl.load_tokenized_prepared_datasets:237] [PID:121] [RANK:0] Processing datasets during training can lead to VRAM instability. Please pre-process your dataset.[39m |
| [2025-12-03 19:59:26,241] [INFO] [axolotl.load_tokenized_prepared_datasets:244] [PID:121] [RANK:0] No seed provided, using default seed of 42[39m |
| [2025-12-03 19:59:31,440] [INFO] [axolotl.get_dataset_wrapper:612] [PID:121] [RANK:0] Loading dataset with base_type: alpaca and prompt_style: None[39m |
| [2025-12-03 19:59:35,953] [INFO] [axolotl.load_tokenized_prepared_datasets:491] [PID:121] [RANK:0] Saving merged prepared dataset to disk... last_run_prepared/c8b534ced2ddf0659aff669f20b527cd[39m |
| [2025-12-03 19:59:35,992] [DEBUG] [axolotl.calculate_total_num_steps:320] [PID:121] [RANK:0] total_num_tokens: 325_153[39m |
| [2025-12-03 19:59:36,008] [DEBUG] [axolotl.calculate_total_num_steps:338] [PID:121] [RANK:0] `total_supervised_tokens: 222_219`[39m |
| [2025-12-03 19:59:36,008] [DEBUG] [axolotl.calculate_total_num_steps:416] [PID:121] [RANK:0] total_num_steps: 475[39m |
| [2025-12-03 19:59:36,008] [INFO] [axolotl.prepare_dataset:152] [PID:121] [RANK:0] Maximum number of steps set at 100[39m |
| [2025-12-03 19:59:36,019] [DEBUG] [axolotl.train.train:66] [PID:121] [RANK:0] loading tokenizer... HuggingFaceTB/SmolLM2-135M[39m |
| [2025-12-03 19:59:36,499] [DEBUG] [axolotl.load_tokenizer:293] [PID:121] [RANK:0] EOS: 0 / <|endoftext|>[39m |
| [2025-12-03 19:59:36,499] [DEBUG] [axolotl.load_tokenizer:294] [PID:121] [RANK:0] BOS: 0 / <|endoftext|>[39m |
| [2025-12-03 19:59:36,499] [DEBUG] [axolotl.load_tokenizer:295] [PID:121] [RANK:0] PAD: 0 / <|endoftext|>[39m |
| [2025-12-03 19:59:36,499] [DEBUG] [axolotl.load_tokenizer:296] [PID:121] [RANK:0] UNK: 0 / <|endoftext|>[39m |
| [2025-12-03 19:59:36,499] [INFO] [axolotl.load_tokenizer:310] [PID:121] [RANK:0] No Chat template selected. Consider adding a chat template for easier inference.[39m |
| [2025-12-03 19:59:36,499] [DEBUG] [axolotl.train.train:98] [PID:121] [RANK:0] loading model and peft_config...[39m |
| [2025-12-03 19:59:40,766] [INFO] [axolotl.load_model:1074] [PID:121] [RANK:0] converting modules to torch.bfloat16 for flash attention[39m |
| trainable params: 460,800 || all params: 134,975,808 || trainable%: 0.3414 |
| [2025-12-03 19:59:40,880] [INFO] [axolotl.load_model:1137] [PID:121] [RANK:0] GPU memory usage after adapters: 0.000GB ()[39m |
| [2025-12-03 19:59:41,944] [INFO] [axolotl.train.train:141] [PID:121] [RANK:0] Pre-saving adapter config to ./outputs/admin_20251203_195913[39m |
| [2025-12-03 19:59:41,993] [INFO] [axolotl.train.train:178] [PID:121] [RANK:0] Starting trainer...[39m |
| [2025-12-03 19:59:43,462] [INFO] [axolotl.callbacks.on_step_end:128] [PID:121] [RANK:0] GPU memory usage while training: 0.272GB (+0.754GB cache, +0.978GB misc)[39m |
| {'loss': 1.7199, 'grad_norm': 0.6013352870941162, 'learning_rate': 0.0002961615786970389, 'epoch': 0.02} |
| {'loss': 1.8633, 'grad_norm': 0.2632163166999817, 'learning_rate': 0.0002778325235483954, 'epoch': 0.04} |
| {'loss': 1.6853, 'grad_norm': 0.43362969160079956, 'learning_rate': 0.00024621123294467096, 'epoch': 0.06} |
| {'loss': 1.8084, 'grad_norm': 0.3705150783061981, 'learning_rate': 0.00020458574054452313, 'epoch': 0.08} |
| {'loss': 1.5581, 'grad_norm': 0.4706592857837677, 'learning_rate': 0.00015728433331716724, 'epoch': 0.11} |
| {'loss': 1.7214, 'grad_norm': 0.4183749854564667, 'learning_rate': 0.00010922548916454855, 'epoch': 0.13} |
| {'loss': 1.7939, 'grad_norm': 0.34439632296562195, 'learning_rate': 6.540644552236401e-05, 'epoch': 0.15} |
| {'loss': 1.5683, 'grad_norm': 0.3492596745491028, 'learning_rate': 3.038357841559191e-05, 'epoch': 0.17} |
| {'loss': 1.505, 'grad_norm': 0.3816680610179901, 'learning_rate': 7.798623006559435e-06, 'epoch': 0.19} |
| {'loss': 1.675, 'grad_norm': 0.3192552626132965, 'learning_rate': 0.0, 'epoch': 0.21} |
| {'eval_loss': 1.6974681615829468, 'eval_runtime': 2.4034, 'eval_samples_per_second': 41.608, 'eval_steps_per_second': 20.804, 'epoch': 0.21} |
| {'train_runtime': 28.1039, 'train_samples_per_second': 14.233, 'train_steps_per_second': 3.558, 'train_loss': 1.6898639583587647, 'epoch': 0.21} |
| [2025-12-03 20:00:10,358] [INFO] [axolotl.train.train:195] [PID:121] [RANK:0] Training Completed!!! Saving pre-trained model to ./outputs/admin_20251203_195913[39m |
|
|
|
|
| === STDERR === |
| 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`. |
| WARNING: BNB_CUDA_VERSION=121 environment variable detected; loading libbitsandbytes_cuda121.so. |
| This can be used to load a bitsandbytes version that is different from the PyTorch CUDA version. |
| If this was unintended set the BNB_CUDA_VERSION variable to an empty string: export BNB_CUDA_VERSION= |
| If you use the manual override make sure the right libcudart.so is in your LD_LIBRARY_PATH |
| For example by adding the following to your .bashrc: export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:<path_to_cuda_dir/lib64 |
|
|
| Using the `WANDB_DISABLED` environment variable is deprecated and will be removed in v5. Use the --report_to flag to control the integrations used for logging result (for instance --report_to none). |
| df: /root/.triton/autotune: No such file or directory |
| Using the `WANDB_DISABLED` environment variable is deprecated and will be removed in v5. Use the --report_to flag to control the integrations used for logging result (for instance --report_to none). |
| Using the `WANDB_DISABLED` environment variable is deprecated and will be removed in v5. Use the --report_to flag to control the integrations used for logging result (for instance --report_to none). |
| Using the `WANDB_DISABLED` environment variable is deprecated and will be removed in v5. Use the --report_to flag to control the integrations used for logging result (for instance --report_to none). |
| Using the `WANDB_DISABLED` environment variable is deprecated and will be removed in v5. Use the --report_to flag to control the integrations used for logging result (for instance --report_to none). |
| /root/miniconda3/envs/py3.11/lib/python3.11/site-packages/pydantic/main.py:464: UserWarning: Pydantic serializer warnings: |
| PydanticSerializationUnexpectedValue(Expected `enum` - serialized value may not be as expected [field_name='lr_scheduler', input_value='cosine', input_type=str]) |
| PydanticSerializationUnexpectedValue(Expected `literal['one_cycle']` - serialized value may not be as expected [field_name='lr_scheduler', input_value='cosine', input_type=str]) |
| return self.__pydantic_serializer__.to_python( |
|
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| Generating train split: 0%| | 0/2000 [00:00<?, ? examples/s] |
| Generating train split: 100%|██████████| 2000/2000 [00:00<00:00, 54614.40 examples/s] |
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| Tokenizing Prompts (num_proc=64): 100%|██████████| 2000/2000 [00:02<00:00, 765.06 examples/s] |
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| Saving the dataset (0/1 shards): 0%| | 0/2000 [00:00<?, ? examples/s] |
| Saving the dataset (1/1 shards): 100%|██████████| 2000/2000 [00:00<00:00, 113427.01 examples/s] |
| Saving the dataset (1/1 shards): 100%|██████████| 2000/2000 [00:00<00:00, 111810.84 examples/s] |
| 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')`. |
| /root/miniconda3/envs/py3.11/lib/python3.11/site-packages/transformers/training_args.py:1559: FutureWarning: `evaluation_strategy` is deprecated and will be removed in version 4.46 of 🤗 Transformers. Use `eval_strategy` instead |
| warnings.warn( |
| /workspace/axolotl/src/axolotl/core/trainer_builder.py:417: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `AxolotlTrainer.__init__`. Use `processing_class` instead. |
| super().__init__(*_args, **kwargs) |
| max_steps is given, it will override any value given in num_train_epochs |
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| 0%| | 0/100 [00:00<?, ?it/s]You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding. |
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