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## Setup Notes |
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For this model, a VM with 2 T4 GPUs was used. |
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To get the training to work on the 2 GPUs (utilize both GPUS simultaneously), the following command was used to initiate training. |
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WORLD_SIZE=2 CUDA_VISIBLE_DEVICES=0,1 torchrun --nproc_per_node=2 --master_port=1234 finetune.py --base_model 'decapoda-research/llama-7b-hf' --data_path 'wikisql' --output_dir './lora-alpaca' --num_epochs 1 --micro_batch_size 32 |
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Note 1. Micro batch size was increased from the default 4 to 32. |
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Note 2. Output directory was initially lora-alpaca and then contents were moved to new folder when initializing git repository. |
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## Log |
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(sqltest) chrisdono4@deep-learning-duo-t4-4:~/alpaca-lora$ WORLD_SIZE=2 CUDA_VISIBLE_DEVICES=0,1 torchrun --nproc_per_node=2 --master_port=1234 finetune.py --base_model 'decapoda-research/lla |
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ma-7b-hf' --data_path 'wikisql' --output_dir './lora-alpaca' --micro_batch_size 32 --num_epochs 1 |
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WARNING:torch.distributed.run: |
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***************************************** |
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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 appli |
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cation as needed. |
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***************************************** |
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===================================BUG REPORT=================================== |
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Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues |
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================================================================================ |
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===================================BUG REPORT=================================== |
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Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues |
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================================================================================ |
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/opt/conda/envs/sqltest/lib/python3.10/site-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: /opt/conda/envs/sqltest did not contain libcudart.so as expected! Searching further path |
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s... |
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warn(msg) |
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CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so |
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CUDA SETUP: Highest compute capability among GPUs detected: 7.5 |
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CUDA SETUP: Detected CUDA version 113 |
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CUDA SETUP: Loading binary /opt/conda/envs/sqltest/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cuda113.so... |
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/opt/conda/envs/sqltest/lib/python3.10/site-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: /opt/conda/envs/sqltest did not contain libcudart.so as expected! Searching further path |
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s... |
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warn(msg) |
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CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so |
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CUDA SETUP: Highest compute capability among GPUs detected: 7.5 |
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CUDA SETUP: Detected CUDA version 113 |
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CUDA SETUP: Loading binary /opt/conda/envs/sqltest/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cuda113.so... |
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Training Alpaca-LoRA model with params: |
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base_model: decapoda-research/llama-7b-hf |
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data_path: wikisql |
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output_dir: ./lora-alpaca |
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batch_size: 128 |
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micro_batch_size: 32 |
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num_epochs: 1 |
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learning_rate: 0.0003 |
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cutoff_len: 256 |
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val_set_size: 2000 |
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lora_r: 8 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_modules: ['q_proj', 'v_proj'] |
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train_on_inputs: True |
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add_eos_token: False |
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group_by_length: False |
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wandb_project: |
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wandb_run_name: |
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wandb_watch: |
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wandb_log_model: |
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resume_from_checkpoint: False |
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prompt template: alpaca |
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Loading checkpoint shards: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 33/33 [01:24<00:00, 2.57s/it] |
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Loading checkpoint shards: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 33/33 [01:25<00:00, 2.58s/it] |
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The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. |
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The tokenizer class you load from this checkpoint is 'LLaMATokenizer'. |
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The class this function is called from is 'LlamaTokenizer'. |
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The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. |
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The tokenizer class you load from this checkpoint is 'LLaMATokenizer'. |
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The class this function is called from is 'LlamaTokenizer'. |
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Found cached dataset wikisql (/home/chrisdono4/.cache/huggingface/datasets/wikisql/default/0.1.0/7037bfe6a42b1ca2b6ac3ccacba5253b1825d31379e9cc626fc79a620977252d) |
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0%| | 0/3 [00:00<?, ?it/s] |
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Found cached dataset wikisql (/home/chrisdono4/.cache/huggingface/datasets/wikisql/default/0.1.0/7037bfe6a42b1ca2b6ac3ccacba5253b1825d31379e9cc626fc79a620977252d) |
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100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 3/3 [00:00<00:00, 39.74it/s] |
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100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 3/3 [00:00<00:00, 26.05it/s] |
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trainable params: 4194304 || all params: 6742609920 || trainable%: 0.06220594176090199 |
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trainable params: 4194304 || all params: 6742609920 || trainable%: 0.06220594176090199 |
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Loading cached split indices for dataset at /home/chrisdono4/.cache/huggingface/datasets/wikisql/default/0.1.0/7037bfe6a42b1ca2b6ac3ccacba5253b1825d31379e9cc626fc79a620977252d/cache-bccdadf40 |
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48a2d5b.arrow and /home/chrisdono4/.cache/huggingface/datasets/wikisql/default/0.1.0/7037bfe6a42b1ca2b6ac3ccacba5253b1825d31379e9cc626fc79a620977252d/cache-f8d5ea283d842b5a.arrow |
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Loading cached split indices for dataset at /home/chrisdono4/.cache/huggingface/datasets/wikisql/default/0.1.0/7037bfe6a42b1ca2b6ac3ccacba5253b1825d31379e9cc626fc79a620977252d/cache-bccdadf40 |
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48a2d5b.arrow and /home/chrisdono4/.cache/huggingface/datasets/wikisql/default/0.1.0/7037bfe6a42b1ca2b6ac3ccacba5253b1825d31379e9cc626fc79a620977252d/cache-f8d5ea283d842b5a.arrow |
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{'loss': 2.0163, 'learning_rate': 2.9999999999999997e-05, 'epoch': 0.02} |
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{'loss': 1.9284, 'learning_rate': 5.9999999999999995e-05, 'epoch': 0.05} |
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{'loss': 1.77, 'learning_rate': 8.999999999999999e-05, 'epoch': 0.07} |
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{'loss': 1.3452, 'learning_rate': 0.00011999999999999999, 'epoch': 0.09} |
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{'loss': 0.9243, 'learning_rate': 0.00015, 'epoch': 0.12} |
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{'loss': 0.8385, 'learning_rate': 0.00017999999999999998, 'epoch': 0.14} |
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{'loss': 0.7986, 'learning_rate': 0.00020999999999999998, 'epoch': 0.16} |
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{'loss': 0.7786, 'learning_rate': 0.00023999999999999998, 'epoch': 0.19} |
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{'loss': 0.75, 'learning_rate': 0.00027, 'epoch': 0.21} |
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{'loss': 0.7389, 'learning_rate': 0.0003, 'epoch': 0.24} |
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{'loss': 0.7248, 'learning_rate': 0.00029076923076923073, 'epoch': 0.26} |
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{'loss': 0.7199, 'learning_rate': 0.0002815384615384615, 'epoch': 0.28} |
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{'loss': 0.7159, 'learning_rate': 0.0002723076923076923, 'epoch': 0.31} |
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{'loss': 0.7029, 'learning_rate': 0.00026307692307692306, 'epoch': 0.33} |
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{'loss': 0.6851, 'learning_rate': 0.0002538461538461538, 'epoch': 0.35} |
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{'loss': 0.6935, 'learning_rate': 0.0002446153846153846, 'epoch': 0.38} |
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{'loss': 0.6737, 'learning_rate': 0.00023538461538461536, 'epoch': 0.4} |
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{'loss': 0.682, 'learning_rate': 0.00022615384615384614, 'epoch': 0.42} |
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{'loss': 0.667, 'learning_rate': 0.0002169230769230769, 'epoch': 0.45} |
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{'loss': 0.6731, 'learning_rate': 0.00020769230769230766, 'epoch': 0.47} |
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{'eval_loss': 0.6641973853111267, 'eval_runtime': 178.902, 'eval_samples_per_second': 11.179, 'eval_steps_per_second': 0.699, 'epoch': 0.47} |
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{'loss': 0.6631, 'learning_rate': 0.00019846153846153844, 'epoch': 0.49} |
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{'loss': 0.6652, 'learning_rate': 0.0001892307692307692, 'epoch': 0.52} |
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{'loss': 0.6591, 'learning_rate': 0.00017999999999999998, 'epoch': 0.54} |
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{'loss': 0.6605, 'learning_rate': 0.00017076923076923074, 'epoch': 0.56} |
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{'loss': 0.653, 'learning_rate': 0.00016153846153846153, 'epoch': 0.59} |
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{'loss': 0.6574, 'learning_rate': 0.00015230769230769228, 'epoch': 0.61} |
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{'loss': 0.6545, 'learning_rate': 0.00014307692307692307, 'epoch': 0.64} |
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{'loss': 0.6328, 'learning_rate': 0.00013384615384615385, 'epoch': 0.66} |
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{'loss': 0.6485, 'learning_rate': 0.0001246153846153846, 'epoch': 0.68} |
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{'loss': 0.6477, 'learning_rate': 0.00011538461538461538, 'epoch': 0.71} |
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{'loss': 0.639, 'learning_rate': 0.00010615384615384615, 'epoch': 0.73} |
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{'loss': 0.6384, 'learning_rate': 9.692307692307692e-05, 'epoch': 0.75} |
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{'loss': 0.6338, 'learning_rate': 8.76923076923077e-05, 'epoch': 0.78} |
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{'loss': 0.6394, 'learning_rate': 7.846153846153845e-05, 'epoch': 0.8} |
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82%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 348/425 [3:57:23<51:48, 40.37s/it] |
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{'loss': 0.6345, 'learning_rate': 6.923076923076922e-05, 'epoch': 0.82} |
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{'loss': 0.6424, 'learning_rate': 5.9999999999999995e-05, 'epoch': 0.85} |
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{'loss': 0.6271, 'learning_rate': 5.0769230769230766e-05, 'epoch': 0.87} |
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{'loss': 0.6267, 'learning_rate': 4.153846153846154e-05, 'epoch': 0.89} |
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{'loss': 0.642, 'learning_rate': 3.230769230769231e-05, 'epoch': 0.92} |
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{'loss': 0.6389, 'learning_rate': 2.3076923076923076e-05, 'epoch': 0.94} |
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{'eval_loss': 0.6302221417427063, 'eval_runtime': 177.453, 'eval_samples_per_second': 11.271, 'eval_steps_per_second': 0.704, 'epoch': 0.94} |
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{'loss': 0.6224, 'learning_rate': 1.3846153846153845e-05, 'epoch': 0.96} |
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{'loss': 0.6361, 'learning_rate': 4.615384615384615e-06, 'epoch': 0.99} |
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100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 425/425 [4:52:00<00:00, 36.53s/it] |
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{'train_runtime': 17520.706, 'train_samples_per_second': 3.102, 'train_steps_per_second': 0.024, 'train_loss': 0.7834248065948486, 'epoch': 1.0} |
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100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 425/425 [4:52:00<00:00, 41.22s/it] |
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