Commit1d288e1

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update some parameters in finetuning bert tutorial

1 parent3967523 commit1d288e1Copy full SHA for 1d288e1

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Lines changed: 2 additions & 2 deletions

Original file line number	Diff line number	Diff line change
`@@ -208,8 +208,8 @@`
`208`	`208`	`" logging_dir='./logs', # directory for storing logs\n",`
`209`	`209`	`" load_best_model_at_end=True, # load the best model when finished training (default metric is loss)\n",`
`210`	`210`	" # but you can specify `metric_for_best_model` argument to change to accuracy or other metric\n",
`211`		`-" logging_steps=200, # log & save weights each logging_steps\n",`
`212`		`-" save_steps=200,\n",`
	`211`	`+" logging_steps=400, # log & save weights each logging_steps\n",`
	`212`	`+" save_steps=400,\n",`
`213`	`213`	" evaluation_strategy=\"steps\", # evaluate each `logging_steps`\n",
`214`	`214`	`")"`
`215`	`215`	`]`

Lines changed: 2 additions & 2 deletions

Original file line number	Diff line number	Diff line change
`@@ -92,8 +92,8 @@ def compute_metrics(pred):`
`92`	`92`	`logging_dir='./logs',# directory for storing logs`
`93`	`93`	`load_best_model_at_end=True,# load the best model when finished training (default metric is loss)`
`94`	`94`	# but you can specify `metric_for_best_model` argument to change to accuracy or other metric
`95`		`-logging_steps=200,# log & save weights each logging_steps`
`96`		`-save_steps=200,`
	`95`	`+logging_steps=400,# log & save weights each logging_steps`
	`96`	`+save_steps=400,`
`97`	`97`	evaluation_strategy="steps",# evaluate each `logging_steps`
`98`	`98`	`)`
`99`	`99`

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