Jonathan Li
commited on
Commit
•
a8ea5b9
1
Parent(s):
927a07e
Add new ordering
Browse files- data/dev.jsonl +2 -2
- data/train.jsonl +2 -2
- data_anon/train.jsonl +1 -1
- process.ipynb +17 -16
data/dev.jsonl
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:b4f71bd11bb0a27021dcd88f2eca9f0400c42f435ec291f7895b4627b63b29f2
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size 21816052
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data/train.jsonl
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:171f91a4c82b362878d06fecc5c8d7a15aa1009b0d84c4427753d8458b7d399e
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size 105354910
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data_anon/train.jsonl
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 98259925
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:0b735134e63256e822ef0115735c59ccfaefe44488ffbfac8f25d80a3385073f
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size 98259925
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process.ipynb
CHANGED
@@ -11,18 +11,18 @@
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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"_dev = pd.read_json(\"
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"_test = pd.read_json(\"
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"_train = pd.read_json(\"
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]
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},
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{
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"cell_type": "code",
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-
"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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@@ -39,7 +39,7 @@
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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@@ -49,7 +49,8 @@
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"d_remaining = {k: v[dist[k]:] for k, v in d.items()}\n",
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"\n",
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"new_rows = []\n",
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"for
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" new_rows.append(train.iloc[d_train[label].pop()])\n",
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"\n",
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"new_train = pd.concat([pd.DataFrame(new_rows), pd.DataFrame(train.iloc[i] for l in d_remaining.values() for i in l).sample(frac=1, random_state=42)])"
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@@ -57,7 +58,7 @@
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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@@ -72,14 +73,14 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"train = pd.read_json(\"
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-
"test = pd.read_json(\"
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"dev = pd.read_json(\"
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]
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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@@ -93,13 +94,13 @@
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},
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{
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"cell_type": "code",
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-
"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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-
"train.to_json(\"train.jsonl\", lines=True, orient=\"records\")\n",
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"test.to_json(\"test.jsonl\", lines=True, orient=\"records\")\n",
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"dev.to_json(\"dev.jsonl\", lines=True, orient=\"records\")"
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]
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}
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],
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"_dev = pd.read_json(\"EN_dev_Anon.jsonl\", lines=True)\n",
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"_test = pd.read_json(\"EN_test_Anon.jsonl\", lines=True)\n",
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"_train = pd.read_json(\"EN_train_Anon.jsonl\", lines=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"d_remaining = {k: v[dist[k]:] for k, v in d.items()}\n",
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"\n",
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"new_rows = []\n",
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"for i in range(len(dev[\"violated\"])):\n",
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" label = i % 2 == 0\n",
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" new_rows.append(train.iloc[d_train[label].pop()])\n",
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"\n",
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"new_train = pd.concat([pd.DataFrame(new_rows), pd.DataFrame(train.iloc[i] for l in d_remaining.values() for i in l).sample(frac=1, random_state=42)])"
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"metadata": {},
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"outputs": [],
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"source": [
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"train = pd.read_json(\"data/train.jsonl\", lines=True, orient=\"records\")\n",
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"test = pd.read_json(\"data/test.jsonl\", lines=True, orient=\"records\")\n",
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"dev = pd.read_json(\"data/dev.jsonl\", lines=True, orient=\"records\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"train.to_json(\"data/train.jsonl\", lines=True, orient=\"records\")\n",
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"test.to_json(\"data/test.jsonl\", lines=True, orient=\"records\")\n",
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"dev.to_json(\"data/dev.jsonl\", lines=True, orient=\"records\")"
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]
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}
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],
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