zsl01670416
71a80173e5
modify examples text_classification, text_generation, token_classification for improved trainer
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1.text_classification/run_train.sh
2.text_generation/run_train_mt5.sh, run_train_palm.sh
3.token_classification/finetune_token_classification.py, run_train_mgeo.sh, run_train_structbert.sh
above files were modified to adapt to improved trainer
Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/12629010
2023-05-16 14:32:43 +08:00
hemu.zp
5804ad2dc1
update multi_modal_embedding example
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Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/12626062
2023-05-16 14:31:26 +08:00
xingjun.wang
98e899b8c2
merge master
2023-05-14 02:09:02 +08:00
yuze.zyz
febc0365de
Support FlexTrain and update the structure of trainer
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1. Refactor training_args
2. Refactor hooks
3. Add train_id for push_to_hub
4. Support both output_dir/output_sub_dir for checkpoint_hooks
5. Support copy when hardlink fails when checkpointing
6. Support mixed dataset config file as a CLI argument
7. Add eval txt in output folder
Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/12384253
* support the ignorance of file pattern
2023-05-13 12:12:04 +08:00
Wang Qiang
9bfc4a9d83
Add finetuning stable diffusion example ( #285 )
2023-04-28 10:18:42 +08:00
hemu
9f2f1c066a
change file names
2023-04-13 10:41:18 +08:00
hemu
672f25266f
Merge branch 'master-github' into master-merge-github-0413
2023-04-13 10:32:01 +08:00
slin000111
92d7eae5b9
add token classification example and gpt3 one layer test ( #268 )
2023-04-13 10:21:00 +08:00
hemu.zp
9940994d72
Add multi-modal embedding example for CLIP
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Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/12251820
2023-04-11 10:12:11 +08:00
yuze.zyz
4040320346
push to hub
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Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/12235855
2023-04-10 18:17:52 +08:00
hemu.zp
dd16c11f2a
Add token classification example for MGeo
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Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/12259147
2023-04-10 17:08:35 +08:00
hemu.zp
f0d69c2aa4
Add palm example
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Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/12259265
2023-04-10 14:55:44 +08:00
hemu.zp
eecdd90412
add finetune_text_generation
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1. Add TrainingArgs and cli call form for text generation task
2. Fix dp+tp finetune bug
Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/11929345
2023-03-10 15:08:56 +08:00
Firmament-cyou
8092a82577
add directory for image_classification finetuneing scripts ( #115 )
2023-02-21 11:33:41 +08:00
hemu.zp
82482b3e96
update training args
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Based on feat/0131/nlp_args branch, the original code review: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/11408570
Support for running finetuning from the command line with training args, Compatible with the configuration optimization.
2023-02-10 05:32:21 +00:00
zhangzhicheng.zzc
42898badf7
[to #42322933 ] update ast_index logic
2023-01-11 10:43:56 +08:00
wenmeng.zwm
b8ec677739
add training args support and image classification fintune example
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design doc: https://yuque.antfin.com/pai/rwqgvl/khy4uw5dgi39s6ke
usage:
```python
from modelscope.trainers.training_args import (ArgAttr, MSArgumentParser,
training_args)
training_args.topk = ArgAttr(cfg_node_name=['train.evaluation.metric_options.topk',
'evaluation.metric_options.topk'],
default=(1,), help='evaluation using topk, tuple format, eg (1,), (1,5)')
training_args.train_data = ArgAttr(type=str, default='tany0699/cats_and_dogs', help='train dataset')
training_args.validation_data = ArgAttr(type=str, default='tany0699/cats_and_dogs', help='validation dataset')
training_args.model_id = ArgAttr(type=str, default='damo/cv_vit-base_image-classification_ImageNet-labels', help='model name')
parser = MSArgumentParser(training_args)
cfg_dict = parser.get_cfg_dict()
args = parser.args
train_dataset = create_dataset(args.train_data, split='train')
val_dataset = create_dataset(args.validation_data, split='validation')
def cfg_modify_fn(cfg):
cfg.merge_from_dict(cfg_dict)
return cfg
kwargs = dict(
model=args.model_id, # model id
train_dataset=train_dataset, # training dataset
eval_dataset=val_dataset, # validation dataset
cfg_modify_fn=cfg_modify_fn # callback to modify configuration
)
trainer = build_trainer(name=Trainers.image_classification, default_args=kwargs)
# start to train
trainer.train()
```
Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/11225071
2022-12-30 07:35:15 +08:00
