train model
Browse files- scripts/train_model.py +4 -4
scripts/train_model.py
CHANGED
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@@ -8,7 +8,7 @@ from transformers import DataCollatorForLanguageModeling
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import torch
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from torch.utils.data import DataLoader
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import torch.multiprocessing as mp
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# x = input('Are you sure? [y/N] ')
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@@ -18,7 +18,7 @@ import torch.multiprocessing as mp
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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mp.set_start_method('spawn', force=True)
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def _batch_iterator():
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@@ -266,7 +266,7 @@ train_dataloader = DataLoader(
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collate_fn=collate_fn,
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batch_size=training_args.per_device_train_batch_size,
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pin_memory=True,
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num_workers=4
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)
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eval_dataloader = DataLoader(
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@@ -274,7 +274,7 @@ eval_dataloader = DataLoader(
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collate_fn=collate_fn,
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batch_size=training_args.per_device_eval_batch_size,
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pin_memory=True,
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num_workers=4
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)
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trainer = Trainer(
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import torch
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from torch.utils.data import DataLoader
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# import torch.multiprocessing as mp
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# x = input('Are you sure? [y/N] ')
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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# mp.set_start_method('spawn', force=True)
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def _batch_iterator():
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collate_fn=collate_fn,
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batch_size=training_args.per_device_train_batch_size,
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pin_memory=True,
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# num_workers=4
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)
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eval_dataloader = DataLoader(
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collate_fn=collate_fn,
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batch_size=training_args.per_device_eval_batch_size,
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pin_memory=True,
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# num_workers=4
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)
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trainer = Trainer(
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