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[feat] update trainer

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jingyaogong 2025-10-28 23:30:10 +08:00
parent eb96113cd4
commit 8f7e07b8ef
9 changed files with 9 additions and 9 deletions
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2
trainer/train_distill_reason.py
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@ -15,7 +15,7 @@ from torch.nn.parallel import DistributedDataParallel
from torch.utils.data import DataLoader, DistributedSampler from torch.utils.data import DataLoader, DistributedSampler
from model.model_minimind import MiniMindConfig from model.model_minimind import MiniMindConfig
from dataset.lm_dataset import SFTDataset from dataset.lm_dataset import SFTDataset
from trainer.trainer_utils import * from trainer.trainer_utils import get_lr, Logger, is_main_process, lm_checkpoint, init_distributed_mode, setup_seed, init_model, SkipBatchSampler
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')

2
trainer/train_distillation.py
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@ -16,7 +16,7 @@ from torch.nn.parallel import DistributedDataParallel
from torch.utils.data import DataLoader, DistributedSampler from torch.utils.data import DataLoader, DistributedSampler
from model.model_minimind import MiniMindConfig from model.model_minimind import MiniMindConfig
from dataset.lm_dataset import SFTDataset from dataset.lm_dataset import SFTDataset
from trainer.trainer_utils import * from trainer.trainer_utils import get_lr, Logger, is_main_process, lm_checkpoint, init_distributed_mode, setup_seed, init_model, SkipBatchSampler
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')

2
trainer/train_dpo.py
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@ -16,7 +16,7 @@ from torch.nn.parallel import DistributedDataParallel
from torch.utils.data import DataLoader, DistributedSampler from torch.utils.data import DataLoader, DistributedSampler
from model.model_minimind import MiniMindConfig from model.model_minimind import MiniMindConfig
from dataset.lm_dataset import DPODataset from dataset.lm_dataset import DPODataset
from trainer.trainer_utils import * from trainer.trainer_utils import get_lr, Logger, is_main_process, lm_checkpoint, init_distributed_mode, setup_seed, init_model, SkipBatchSampler
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')

2
trainer/train_full_sft.py
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@ -15,7 +15,7 @@ from torch.nn.parallel import DistributedDataParallel
from torch.utils.data import DataLoader, DistributedSampler from torch.utils.data import DataLoader, DistributedSampler
from model.model_minimind import MiniMindConfig from model.model_minimind import MiniMindConfig
from dataset.lm_dataset import SFTDataset from dataset.lm_dataset import SFTDataset
from trainer.trainer_utils import * from trainer.trainer_utils import get_lr, Logger, is_main_process, lm_checkpoint, init_distributed_mode, setup_seed, init_model, SkipBatchSampler
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')

2
trainer/train_grpo.py
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@ -19,7 +19,7 @@ from torch.optim.lr_scheduler import CosineAnnealingLR
from transformers import AutoModel from transformers import AutoModel
from model.model_minimind import MiniMindConfig, MiniMindForCausalLM from model.model_minimind import MiniMindConfig, MiniMindForCausalLM
from dataset.lm_dataset import RLAIFDataset from dataset.lm_dataset import RLAIFDataset
from trainer.trainer_utils import * from trainer.trainer_utils import Logger, is_main_process, lm_checkpoint, init_distributed_mode, setup_seed, SkipBatchSampler
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')

2
trainer/train_lora.py
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@ -16,7 +16,7 @@ from torch.utils.data import DataLoader, DistributedSampler
from model.model_minimind import MiniMindConfig from model.model_minimind import MiniMindConfig
from dataset.lm_dataset import SFTDataset from dataset.lm_dataset import SFTDataset
from model.model_lora import save_lora, apply_lora from model.model_lora import save_lora, apply_lora
from trainer.trainer_utils import * from trainer.trainer_utils import get_lr, Logger, is_main_process, lm_checkpoint, init_distributed_mode, setup_seed, init_model, SkipBatchSampler
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')

2
trainer/train_ppo.py
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@ -20,7 +20,7 @@ from torch.optim.lr_scheduler import CosineAnnealingLR
from transformers import AutoModel from transformers import AutoModel
from model.model_minimind import MiniMindConfig, MiniMindForCausalLM from model.model_minimind import MiniMindConfig, MiniMindForCausalLM
from dataset.lm_dataset import RLAIFDataset from dataset.lm_dataset import RLAIFDataset
from trainer.trainer_utils import * from trainer.trainer_utils import Logger, is_main_process, lm_checkpoint, init_distributed_mode, setup_seed, SkipBatchSampler
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')

2
trainer/train_pretrain.py
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@ -15,7 +15,7 @@ from torch.nn.parallel import DistributedDataParallel
from torch.utils.data import DataLoader, DistributedSampler from torch.utils.data import DataLoader, DistributedSampler
from model.model_minimind import MiniMindConfig from model.model_minimind import MiniMindConfig
from dataset.lm_dataset import PretrainDataset from dataset.lm_dataset import PretrainDataset
from trainer.trainer_utils import * from trainer.trainer_utils import get_lr, Logger, is_main_process, lm_checkpoint, init_distributed_mode, setup_seed, init_model, SkipBatchSampler
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')

2
trainer/train_spo.py
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@ -19,7 +19,7 @@ from torch.optim.lr_scheduler import CosineAnnealingLR
from transformers import AutoModel from transformers import AutoModel
from model.model_minimind import MiniMindConfig, MiniMindForCausalLM from model.model_minimind import MiniMindConfig, MiniMindForCausalLM
from dataset.lm_dataset import RLAIFDataset from dataset.lm_dataset import RLAIFDataset
from trainer.trainer_utils import * from trainer.trainer_utils import Logger, is_main_process, lm_checkpoint, init_distributed_mode, setup_seed, SkipBatchSampler
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')