fix elmo examples

Ubuntu · Ubuntu · commit 92d1f3fe92bc · 2018-12-15T10:32:12.000Z
diff --git a/examples_elmo/factrueval-nmt.ipynb b/examples_elmo/factrueval-nmt.ipynb
@@ -234,9 +234,11 @@
     }
    ],
    "source": [
+    "num_epochs = 100\n",
     "learner = NerLearner(model, data,\n",
     "                     best_model_path=\"/datadrive/models/factrueval/elmo_attn_nmt.cpt\",\n",
-    "                     base_lr=0.001, lr_max=0.005, clip=5.0, use_lr_scheduler=False, sup_labels=data.id2label[4:])"
+    "                     lr=0.01, clip=1.0, sup_labels=data.id2label[4:],\n",
+    "                     t_total=num_epochs * len(data.train_dl))"
    ]
   },
   {
@@ -255,7 +257,7 @@
    },
    "outputs": [],
    "source": [
-    "learner.fit(100, target_metric='prec')"
+    "learner.fit(num_epochs, target_metric='prec')"
    ]
   },
   {
diff --git a/examples_elmo/factrueval.ipynb b/examples_elmo/factrueval.ipynb
@@ -238,9 +238,11 @@
     }
    ],
    "source": [
+    "num_epochs = 100\n",
     "learner = NerLearner(model, data,\n",
     "                     best_model_path=\"/datadrive/models/factrueval/elmo_attn_cased.cpt\",\n",
-    "                     base_lr=0.0001, lr_max=0.005, clip=5.0, use_lr_scheduler=True, sup_labels=data.id2label[4:])"
+    "                     lr=0.01, clip=1.0, sup_labels=data.id2label[4:],\n",
+    "                     t_total=num_epochs * len(data.train_dl))"
    ]
   },
   {
@@ -347,7 +349,7 @@
     }
    ],
    "source": [
-    "learner.fit(1, target_metric='prec')"
+    "learner.fit(num_epochs, target_metric='f1')"
    ]
   },
   {
diff --git a/examples_elmo/samples.ipynb b/examples_elmo/samples.ipynb

Original file line number	Diff line number	Diff line change
`@@ -234,9 +234,11 @@`
`234`	`234`	`}`
`235`	`235`	`],`
`236`	`236`	`"source": [`
	`237`	`+ "num_epochs = 100\n",`
`237`	`238`	`"learner = NerLearner(model, data,\n",`
`238`	`239`	`" best_model_path=\"/datadrive/models/factrueval/elmo_attn_nmt.cpt\",\n",`
`239`		`- " base_lr=0.001, lr_max=0.005, clip=5.0, use_lr_scheduler=False, sup_labels=data.id2label[4:])"`
	`240`	`+ " lr=0.01, clip=1.0, sup_labels=data.id2label[4:],\n",`
	`241`	`+ " t_total=num_epochs * len(data.train_dl))"`
`240`	`242`	`]`
`241`	`243`	`},`
`242`	`244`	`{`
`@@ -255,7 +257,7 @@`
`255`	`257`	`},`
`256`	`258`	`"outputs": [],`
`257`	`259`	`"source": [`
`258`		`- "learner.fit(100, target_metric='prec')"`
	`260`	`+ "learner.fit(num_epochs, target_metric='prec')"`
`259`	`261`	`]`
`260`	`262`	`},`
`261`	`263`	`{`
Original file line number	Diff line number	Diff line change
`@@ -238,9 +238,11 @@`
`238`	`238`	`}`
`239`	`239`	`],`
`240`	`240`	`"source": [`
	`241`	`+ "num_epochs = 100\n",`
`241`	`242`	`"learner = NerLearner(model, data,\n",`
`242`	`243`	`" best_model_path=\"/datadrive/models/factrueval/elmo_attn_cased.cpt\",\n",`
`243`		`- " base_lr=0.0001, lr_max=0.005, clip=5.0, use_lr_scheduler=True, sup_labels=data.id2label[4:])"`
	`244`	`+ " lr=0.01, clip=1.0, sup_labels=data.id2label[4:],\n",`
	`245`	`+ " t_total=num_epochs * len(data.train_dl))"`
`244`	`246`	`]`
`245`	`247`	`},`
`246`	`248`	`{`
`@@ -347,7 +349,7 @@`
`347`	`349`	`}`
`348`	`350`	`],`
`349`	`351`	`"source": [`
`350`		`- "learner.fit(1, target_metric='prec')"`
	`352`	`+ "learner.fit(num_epochs, target_metric='f1')"`
`351`	`353`	`]`
`352`	`354`	`},`
`353`	`355`	`{`