Upload 12 files
Browse files- rxn/model/added_tokens.json +79 -0
- rxn/model/all_results.json +7 -0
- rxn/model/cfg.py +112 -0
- rxn/model/config.json +33 -0
- rxn/model/generation_config.json +10 -0
- rxn/model/pytorch_model.bin.index.json +873 -0
- rxn/model/special_tokens_map.json +24 -0
- rxn/model/tokenizer.model +3 -0
- rxn/model/tokenizer_config.json +33 -0
- rxn/model/train_results.json +7 -0
- rxn/model/trainer_state.json +1345 -0
- rxn/model/trainer_state.png +0 -0
rxn/model/added_tokens.json
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"<Age>": 32011,
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"<Cnd/ed>": 32007,
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"<Cnd/st>": 32006,
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"<ID_10>": 32025,
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"<ID_11>": 32026,
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"<ID_12>": 32027,
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"<ID_13>": 32028,
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"<ID_14>": 32029,
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"<ID_15>": 32030,
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"<ID_16>": 32031,
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"<ID_17>": 32032,
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"<ID_18>": 32033,
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"<ID_19>": 32034,
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"<ID_1>": 32016,
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"<ID_20>": 32035,
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"<ID_21>": 32036,
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"<ID_22>": 32037,
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"<ID_23>": 32038,
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"<ID_24>": 32039,
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"<ID_25>": 32040,
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"<ID_26>": 32041,
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"<ID_27>": 32042,
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"<ID_28>": 32043,
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"<ID_29>": 32044,
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"<ID_2>": 32017,
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"<ID_30>": 32045,
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"<ID_31>": 32046,
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"<ID_32>": 32047,
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"<ID_33>": 32048,
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"<ID_34>": 32049,
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"<ID_35>": 32050,
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"<ID_36>": 32051,
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"<ID_37>": 32052,
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"<ID_38>": 32053,
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"<ID_39>": 32054,
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"<ID_3>": 32018,
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"<ID_40>": 32055,
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"<ID_41>": 32056,
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"<ID_42>": 32057,
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"<ID_43>": 32058,
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"<ID_44>": 32059,
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"<ID_45>": 32060,
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"<ID_46>": 32061,
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"<ID_47>": 32062,
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"<ID_48>": 32063,
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"<ID_49>": 32064,
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"<ID_4>": 32019,
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"<ID_50>": 32065,
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"<ID_5>": 32020,
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"<ID_6>": 32021,
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"<ID_7>": 32022,
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"<ID_8>": 32023,
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"<ID_9>": 32024,
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"<Obj>": 32015,
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"<Prd/ed>": 32005,
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"<Prd/st>": 32004,
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"<Prd/st> ": 32069,
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"<Rct/ed>": 32003,
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"<Rct/st>": 32002,
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"<Rxn/ed>": 32001,
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"<Rxn/st>": 32000,
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"<Sol>": 32010,
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"<Str>": 32008,
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"<Tem>": 32012,
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"<Tme>": 32013,
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"<Txt>": 32009,
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"<Yld>": 32014,
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"<im_end>": 32068,
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"<im_patch>": 32066,
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"<im_start>": 32067,
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"[Age]": 32073,
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"[Obj]": 32076,
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"[Sol]": 32072,
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"[Str]": 32070,
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"[Tem]": 32074,
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"[Txt]": 32071,
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"[Yld]": 32075
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}
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rxn/model/all_results.json
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{
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"epoch": 50.0,
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"train_loss": 0.13681490471417254,
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"train_runtime": 4969.2412,
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"train_samples_per_second": 13.865,
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"train_steps_per_second": 0.443
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}
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rxn/model/cfg.py
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DEFAULT_TEST_DATASET = dict(
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flickr=dict(
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filename='./reactiondata/real_test.jsonl',
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image_folder='./reaction_image',
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template_file='./config/_base_/dataset/template/reaction.json',
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type='FlickrDataset'),
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reg=dict(
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filename='./reactiondata/train_OCR.jsonl',
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image_folder='./reaction_image_OCR',
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template_file='./config/_base_/dataset/template/OCR.json',
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type='REGDataset'))
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DEFAULT_TRAIN_DATASET = dict(
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flickr=dict(
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filename='./reactiondata/reaction_real_structed.jsonl',
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image_folder='./reaction_image',
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template_file='./config/_base_/dataset/template/reaction.json',
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type='FlickrDataset'),
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reg=dict(
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filename='./reactiondata/train_OCR.jsonl',
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image_folder='./reaction_image_OCR',
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template_file='./config/_base_/dataset/template/OCR.json',
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type='REGDataset'))
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data_args = dict(
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collator_kwargs=dict(max_length=1024, padding=True),
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compute_metric=None,
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gen_kwargs=dict(max_new_tokens=1024, num_beams=1),
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test=None,
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train=dict(
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cfgs=[
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dict(
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filename='./reactiondata/train_OCR.jsonl',
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image_folder='./reaction_image_OCR',
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template_file='./config/_base_/dataset/template/OCR.json',
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type='REGDataset'),
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dict(
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filename='./reactiondata/reaction_real_structed.jsonl',
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image_folder='./reaction_image',
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template_file='./config/_base_/dataset/template/reaction.json',
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type='FlickrDataset'),
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],
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probabilities=[
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0.0,
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1,
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],
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seed=None,
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stopping_strategy='first_exhausted',
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type='InterleaveDateset'),
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validation=dict(
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cfgs=[
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dict(
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filename='./reactiondata/real_test.jsonl',
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image_folder='./reaction_image',
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template_file='./config/_base_/dataset/template/reaction.json',
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type='FlickrDataset'),
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],
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type='ConcatDatasetWithShuffle'))
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| 57 |
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model_args = dict(
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cache_dir=None,
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conv_args=dict(
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conv_template='vicuna_v1.1',
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tokenize_kwargs=dict(truncation_size=2048)),
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freeze_backbone=False,
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| 63 |
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freeze_mm_mlp_adapter=False,
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gen_kwargs_set_bos_token_id=True,
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gen_kwargs_set_eos_token_id=True,
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gen_kwargs_set_pad_token_id=True,
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| 67 |
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image_token_len=300,
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mm_use_im_start_end=True,
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mm_vision_select_layer=-2,
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model_max_length=2048,
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model_name_or_path='./exp/reaction_4.2.1',
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pretrain_mm_mlp_adapter=None,
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process_func_args=dict(
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| 74 |
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conv=dict(type='ShikraConvProcess'),
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| 75 |
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image=dict(type='ShikraImageProcessor'),
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target=dict(type='BoxFormatProcess'),
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| 77 |
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text=dict(type='ShikraTextProcess')),
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| 78 |
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sep_image_conv_front=False,
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| 79 |
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target_processor=dict(boxes=dict(type='PlainBoxFormatter')),
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| 80 |
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tune_mm_mlp_adapter=False,
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| 81 |
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type='shikra',
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| 82 |
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version='v1',
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| 83 |
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vision_tower='SenseTime/deformable-detr')
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| 84 |
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training_args = dict(
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| 85 |
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bf16=True,
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| 86 |
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dataloader_num_workers=4,
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| 87 |
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do_eval=False,
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| 88 |
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do_predict=False,
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| 89 |
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do_train=True,
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| 90 |
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evaluation_strategy='no',
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| 91 |
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fsdp='full_shard auto_wrap',
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| 92 |
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fsdp_transformer_layer_cls_to_wrap='LlamaDecoderLayer',
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| 93 |
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gradient_accumulation_steps=1,
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| 94 |
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gradient_checkpointing=True,
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| 95 |
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learning_rate=2e-05,
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| 96 |
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logging_steps=10,
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| 97 |
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lr_scheduler_type='cosine',
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| 98 |
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num_train_epochs=50,
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| 99 |
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output_dir='./exp/reaction_4.2.2-large',
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| 100 |
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overwrite_output_dir=False,
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| 101 |
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per_device_eval_batch_size=4,
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| 102 |
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per_device_train_batch_size=4,
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| 103 |
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predict_with_generate=True,
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| 104 |
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remove_unused_columns=False,
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| 105 |
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report_to='none',
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| 106 |
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save_steps=10000,
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| 107 |
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save_strategy='steps',
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| 108 |
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save_total_limit=1,
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| 109 |
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seed=42,
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| 110 |
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tf32=True,
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| 111 |
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warmup_ratio=0.03,
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| 112 |
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weight_decay=0.05)
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rxn/model/config.json
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{
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| 2 |
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"_name_or_path": "./exp/reaction_4.2.1",
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| 3 |
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"architectures": [
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| 4 |
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"ShikraLlamaForCausalLM"
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| 5 |
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],
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| 6 |
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"bos_token_id": 1,
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| 7 |
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"eos_token_id": 2,
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| 8 |
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"freeze_mm_mlp_adapter": false,
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| 9 |
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"hidden_act": "silu",
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| 10 |
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"hidden_size": 4096,
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| 11 |
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"initializer_range": 0.02,
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| 12 |
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"intermediate_size": 11008,
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| 13 |
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"max_position_embeddings": 4096,
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| 14 |
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"mm_hidden_size": 256,
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| 15 |
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"mm_use_im_start_end": true,
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| 16 |
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"mm_vision_select_layer": -2,
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| 17 |
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"mm_vision_tower": "SenseTime/deformable-detr",
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| 18 |
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"model_type": "shikra",
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| 19 |
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"num_attention_heads": 32,
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| 20 |
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"num_hidden_layers": 32,
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| 21 |
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"num_key_value_heads": 32,
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| 22 |
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"pad_token_id": 0,
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| 23 |
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"pretraining_tp": 1,
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| 24 |
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"rms_norm_eps": 1e-05,
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| 25 |
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"rope_scaling": null,
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| 26 |
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"tie_word_embeddings": false,
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| 27 |
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"torch_dtype": "float32",
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| 28 |
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"transformers_version": "4.28.0.dev0",
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| 29 |
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"tune_mm_mlp_adapter": false,
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| 30 |
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"use_cache": false,
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| 31 |
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"use_mm_proj": true,
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| 32 |
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"vocab_size": 32077
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| 33 |
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}
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rxn/model/generation_config.json
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{
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"bos_token_id": 1,
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| 3 |
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"do_sample": true,
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| 4 |
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"eos_token_id": 2,
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| 5 |
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"max_length": 4096,
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| 6 |
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"pad_token_id": 0,
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| 7 |
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"temperature": 0.6,
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| 8 |
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"top_p": 0.9,
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| 9 |
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"transformers_version": "4.28.0.dev0"
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| 10 |
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}
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rxn/model/pytorch_model.bin.index.json
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|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 27120484136
|
| 4 |
+
},
|
| 5 |
+
"weight_map": {
|
| 6 |
+
"lm_head.weight": "pytorch_model-00003-of-00003.bin",
|
| 7 |
+
"model.embed_tokens.weight": "pytorch_model-00001-of-00003.bin",
|
| 8 |
+
"model.layers.0.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
| 9 |
+
"model.layers.0.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
|
| 10 |
+
"model.layers.0.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
|
| 11 |
+
"model.layers.0.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
|
| 12 |
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"model.layers.0.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
| 13 |
+
"model.layers.0.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
|
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rxn/model/special_tokens_map.json
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| 23 |
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rxn/model/tokenizer.model
ADDED
|
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rxn/model/tokenizer_config.json
ADDED
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| 31 |
+
"single_word": false
|
| 32 |
+
}
|
| 33 |
+
}
|
rxn/model/train_results.json
ADDED
|
@@ -0,0 +1,7 @@
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|
| 1 |
+
{
|
| 2 |
+
"epoch": 50.0,
|
| 3 |
+
"train_loss": 0.13681490471417254,
|
| 4 |
+
"train_runtime": 4969.2412,
|
| 5 |
+
"train_samples_per_second": 13.865,
|
| 6 |
+
"train_steps_per_second": 0.443
|
| 7 |
+
}
|
rxn/model/trainer_state.json
ADDED
|
@@ -0,0 +1,1345 @@
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