wandb/run-20240515_121902-us3spl8s/files/output.log

wandb: WARNING Saving files without folders. If you want to preserve subdirectories pass base_path to wandb.save, i.e. wandb.save("/mnt/folder/file.h5", base_path="/mnt")
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/root/miniconda3/envs/py3.10/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
[2024-05-15 12:19:40,452] [INFO] [axolotl.callbacks.on_train_begin:770] [PID:13671] [RANK:0] The Axolotl config has been saved to the WandB run under files.
[2024-05-15 12:19:41,543] [INFO] [axolotl.utils.samplers.multipack._len_est:184] [PID:13671] [RANK:0] packing_efficiency_estimate: 0.92 total_num_tokens per device: 47609834
[2024-05-15 12:19:42,607] [INFO] [axolotl.utils.samplers.multipack._len_est:184] [PID:13671] [RANK:0] packing_efficiency_estimate: 0.92 total_num_tokens per device: 47609834
/root/miniconda3/envs/py3.10/lib/python3.10/site-packages/deepspeed/runtime/zero/stage_1_and_2.py:1290: UserWarning: The torch.cuda.*DtypeTensor constructors are no longer recommended. It's best to use methods such as torch.tensor(data, dtype=*, device='cuda') to create tensors. (Triggered internally at ../torch/csrc/tensor/python_tensor.cpp:83.)
  total_norm_cuda = get_accelerator().FloatTensor([float(total_norm)])
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[2024-05-15 12:20:52,036] [INFO] [axolotl.callbacks.on_step_end:125] [PID:13671] [RANK:0] GPU memory usage while training: 16.077GB (+26.679GB cache, +1.247GB misc)
{'loss': 2.2459, 'grad_norm': 55.8736017722144, 'learning_rate': 3.480682213713888e-08, 'epoch': 0.0}


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