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5126c18 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | model training desc: initialize model training...
2023-12-30 17:59:51.341 | INFO | __main__:init_components:108 - Initializing components...
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You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. If you see this, DO NOT PANIC! This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thouroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
2023-12-30 18:00:03.415 | INFO | __main__:init_components:155 -
2023-12-30 18:00:03.415 | INFO | __main__:init_components:156 - ********************
2023-12-30 18:00:03.415 | INFO | __main__:init_components:157 - using llama2 model
2023-12-30 18:00:03.415 | INFO | __main__:init_components:158 - ********************
2023-12-30 18:00:03.415 | INFO | __main__:init_components:159 -
memory footprint of model: 4.024436950683594 GB
trainable params: 319,815,680 || all params: 7,058,231,296 || trainable%: 4.531102291607305
2023-12-30 18:00:48.703 | INFO | component.dataset:__init__:14 - Loading data: /data0/maqi/KGLQA-data/datasets/QuALITY/Caption/quality_caption_and_rel_instruct/train.jsonl
2023-12-30 18:00:48.807 | INFO | component.dataset:__init__:19 - there are 2523 data in dataset
2023-12-30 18:00:49.225 | INFO | __main__:main:231 - *** starting training ***
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{'loss': 0.4754, 'learning_rate': 0.0001, 'global_step': 200, 'epoch': 0.95}
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96%|█████████▌| 201/210 [1:39:22<04:36, 30.70s/it]
96%|█████████▌| 202/210 [1:39:51<04:02, 30.31s/it]
97%|█████████▋| 203/210 [1:40:21<03:30, 30.05s/it]
97%|█████████▋| 204/210 [1:40:50<02:59, 29.86s/it]
98%|█████████▊| 205/210 [1:41:20<02:28, 29.73s/it]
98%|█████████▊| 206/210 [1:41:49<01:58, 29.64s/it]
99%|█████████▊| 207/210 [1:42:19<01:28, 29.58s/it]
99%|█████████▉| 208/210 [1:42:48<00:59, 29.53s/it]
100%|█████████▉| 209/210 [1:43:24<00:31, 31.55s/it]
100%|██████████| 210/210 [1:43:54<00:00, 30.92s/it]
{'loss': 0.4733, 'learning_rate': 0.0001, 'global_step': 210, 'epoch': 1.0}
100%|██████████| 210/210 [1:43:54<00:00, 30.92s/it]
{'train_runtime': 6234.3462, 'train_samples_per_second': 0.405, 'train_steps_per_second': 0.034, 'train_loss': 0.4878490357171921, 'epoch': 1.0}
100%|██████████| 210/210 [1:43:54<00:00, 30.92s/it]
100%|██████████| 210/210 [1:43:54<00:00, 29.69s/it]
***** train metrics *****
epoch = 1.0
train_loss = 0.4878
train_runtime = 1:43:54.34
train_samples_per_second = 0.405
train_steps_per_second = 0.034
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