training_log.txt

[2024-01-10 03:41:18,555] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-01-10 03:41:20,266] [WARNING] [runner.py:203:fetch_hostfile] Unable to find hostfile, will proceed with training with local resources only.
[2024-01-10 03:41:20,266] [INFO] [runner.py:570:main] cmd = /root/anaconda3/envs/dj_comp/bin/python -u -m deepspeed.launcher.launch --world_info=eyJsb2NhbGhvc3QiOiBbMCwgMSwgMiwgMywgNCwgNSwgNiwgN119 --master_addr=127.0.0.1 --master_port=50000 --enable_each_rank_log=None train.py --model_name_or_path /home/baaidial/models/llama-2-13b-hf/ --tokenizer /home/baaidial/models/llama-2-13b-hf/ --data_path /home/baaidial/fengduanyu/lima_code/code/data/alpaca/alpaca_predata.jsonl --output_dir /home/baaidial/fengduanyu/lima_code/code/model_save/after_sft/alpaca_Llama-2-13b_all/ --per_device_train_batch_size 8 --gradient_accumulation_steps 4 --lang en --bf16 True --gradient_checkpointing_enable True --num_train_epochs 3 --model_max_length 1024 --learning_rate 2.5e-5 --weight_decay 0 --warmup_ratio 0.03 --evaluation_strategy no --save_strategy no --save_steps -1 --save_total_limit 999 --lr_scheduler_type cosine --logging_steps 1 --tf32 True --deepspeed /home/baaidial/fengduanyu/FT-Data-Ranker/competition_kit/lm-training/train_scripts/deepspeed_configs/ds_config_stage3.json
[2024-01-10 03:41:21,810] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-01-10 03:41:23,124] [INFO] [launch.py:138:main] 0 NCCL_VERSION=2.18.1
[2024-01-10 03:41:23,124] [INFO] [launch.py:145:main] WORLD INFO DICT: {'localhost': [0, 1, 2, 3, 4, 5, 6, 7]}
[2024-01-10 03:41:23,124] [INFO] [launch.py:151:main] nnodes=1, num_local_procs=8, node_rank=0
[2024-01-10 03:41:23,124] [INFO] [launch.py:162:main] global_rank_mapping=defaultdict(<class 'list'>, {'localhost': [0, 1, 2, 3, 4, 5, 6, 7]})
[2024-01-10 03:41:23,124] [INFO] [launch.py:163:main] dist_world_size=8
[2024-01-10 03:41:23,124] [INFO] [launch.py:165:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
[2024-01-10 03:41:25,938] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-01-10 03:41:26,237] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-01-10 03:41:26,239] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-01-10 03:41:26,338] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-01-10 03:41:26,339] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-01-10 03:41:26,351] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-01-10 03:41:26,353] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-01-10 03:41:26,357] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-01-10 03:41:27,429] [INFO] [comm.py:637:init_distributed] cdb=None
[2024-01-10 03:41:27,429] [INFO] [comm.py:668:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
[2024-01-10 03:41:27,709] [INFO] [comm.py:637:init_distributed] cdb=None
[2024-01-10 03:41:27,773] [INFO] [comm.py:637:init_distributed] cdb=None
[2024-01-10 03:41:27,835] [INFO] [comm.py:637:init_distributed] cdb=None
[2024-01-10 03:41:27,866] [INFO] [comm.py:637:init_distributed] cdb=None
[2024-01-10 03:41:27,867] [INFO] [comm.py:637:init_distributed] cdb=None
[2024-01-10 03:41:27,894] [INFO] [comm.py:637:init_distributed] cdb=None
[2024-01-10 03:41:27,933] [INFO] [comm.py:637:init_distributed] cdb=None
Loading model from /home/baaidial/models/llama-2-13b-hf/
[2024-01-10 03:41:30,329] [INFO] [partition_parameters.py:347:__exit__] finished initializing model - num_params = 363, num_elems = 13.02B
gradient_checkpointing_enable
Model class: <class 'transformers.models.llama.modeling_llama.LlamaForCausalLM'>
Tokenizer class: <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>
+---------+---------+------------+---------+------------+---------+------------+---------+------------+----------------+
|         |pad_token|pad_token_id|bos_token|bos_token_id|eos_token|eos_token_id|unk_token|unk_token_id|model_max_length|
+---------+---------+------------+---------+------------+---------+------------+---------+------------+----------------+
|tokenizer|  <unk>  |     0      |   <s>   |     1      |   </s>  |     2      |  <unk>  |     0      |      1024      |
+---------+---------+------------+---------+------------+---------+------------+---------+------------+----------------+
|  model  |    -    |     0      |    -    |     1      |    -    |     2      |    -    |     -      |       -        |
+---------+---------+------------+---------+------------+---------+------------+---------+------------+----------------+
There are 52002 training samples in data path
Formatting inputs...
Tokenizing inputs... This may take some time...
PROMPT:
'Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\nWhen did the Second World War end?\n\n### Response:'
RESPONSE:
'The Second World War ended on September 2, 1945 with the official surrender of Japan. The Allies officially declared victory over Germany on May 8, 1945, which is known as V-E Day, or Victory in Europe Day.</s>'
====================================================================================================
PROMPT:
'Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\nExplain why the following statement is wrong: "Cloud computing stores your data on the Internet."\n\n### Response:'
RESPONSE:
'The statement is incorrect because cloud computing does not store data on the Internet. Instead, cloud computing stores data in a remote server which is usually connected to the Internet. Data can be accessed and retrieved from the remote server through the Internet using an application.</s>'
====================================================================================================
PROMPT:
'Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\nIdentify 5 major differences between two similar items.\n\n### Input:\nBlackberry and Raspberry\n\n### Response:'
RESPONSE:
'1. Blackberries have a rounded shape, while raspberries have a distinct hollow core when picked off the plant.\n2. Raspberries have a rich and intense flavor profile, while blackberries are sweeter and less tart.\n3. Blackberries typically have very tiny seeds that are barely noticeable when eaten, while raspberries have larger, more noticeable seeds.\n4. Blackberries tend to be darker in color than raspberries, which tend to be a pinkish-red.\n5. Raspberries are generally more fragile, and can spoil or bruise more easily than blackberries.</s>'
====================================================================================================
PROMPT:
'Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\nClassify the following text as opinion, fact, or non-credible\n\n### Input:\nThis new book is amazing!\n\n### Response:'
RESPONSE:
'Opinion.</s>'
====================================================================================================
PROMPT:
'Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\nClean the HTML code by removing all the unnecessary tags.\n\n### Input:\n<html><head><title>Website</title></head><body><p>This is a paragraph.</p><p>This is the second paragraph.</p></body></html>\n\n### Response:'
RESPONSE:
'<html><head><title>Website</title></head><body>This is a paragraph.<p>This is the second paragraph.</p></body></html></s>'
====================================================================================================
ORI NUMBER: 52002, AFTER FILETER: 52000, DROP NUMBER: 2
Total 52000 samples [ 6.56M tokens] in training!
Parameter Offload: Total persistent parameters: 414720 in 81 params
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{'loss': 0.2426, 'learning_rate': 0.0, 'epoch': 3.0}
{'train_runtime': 5691.3236, 'train_samples_per_second': 27.41, 'train_steps_per_second': 0.107, 'train_loss': 0.6601732866517429, 'epoch': 3.0}
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Finish training...
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