model update
Browse files
README.md
CHANGED
@@ -46,236 +46,242 @@ model-index:
|
|
46 |
- name: MoverScore
|
47 |
type: moverscore
|
48 |
value: 0.6499011626820898
|
|
|
|
|
|
|
|
|
|
|
|
|
49 |
- task:
|
50 |
name: Text2text Generation
|
51 |
type: text2text-generation
|
52 |
dataset:
|
53 |
-
name: lmqg/
|
54 |
-
type:
|
55 |
-
args:
|
56 |
metrics:
|
57 |
- name: BLEU4
|
58 |
type: bleu4
|
59 |
-
value:
|
60 |
- name: ROUGE-L
|
61 |
type: rouge-l
|
62 |
-
value: 0.
|
63 |
- name: METEOR
|
64 |
type: meteor
|
65 |
-
value: 0.
|
66 |
- name: BERTScore
|
67 |
type: bertscore
|
68 |
-
value: 0.
|
69 |
- name: MoverScore
|
70 |
type: moverscore
|
71 |
-
value: 0.
|
72 |
- task:
|
73 |
name: Text2text Generation
|
74 |
type: text2text-generation
|
75 |
dataset:
|
76 |
name: lmqg/qg_squadshifts
|
77 |
-
type:
|
78 |
-
args:
|
79 |
metrics:
|
80 |
- name: BLEU4
|
81 |
type: bleu4
|
82 |
-
value: 0.
|
83 |
- name: ROUGE-L
|
84 |
type: rouge-l
|
85 |
-
value: 0.
|
86 |
- name: METEOR
|
87 |
type: meteor
|
88 |
-
value: 0.
|
89 |
- name: BERTScore
|
90 |
type: bertscore
|
91 |
-
value: 0.
|
92 |
- name: MoverScore
|
93 |
type: moverscore
|
94 |
-
value: 0.
|
95 |
- task:
|
96 |
name: Text2text Generation
|
97 |
type: text2text-generation
|
98 |
dataset:
|
99 |
name: lmqg/qg_subjqa
|
100 |
-
type:
|
101 |
-
args:
|
102 |
metrics:
|
103 |
- name: BLEU4
|
104 |
type: bleu4
|
105 |
-
value:
|
106 |
- name: ROUGE-L
|
107 |
type: rouge-l
|
108 |
-
value: 0.
|
109 |
- name: METEOR
|
110 |
type: meteor
|
111 |
-
value: 0.
|
112 |
- name: BERTScore
|
113 |
type: bertscore
|
114 |
-
value: 0.
|
115 |
- name: MoverScore
|
116 |
type: moverscore
|
117 |
-
value: 0.
|
118 |
- task:
|
119 |
name: Text2text Generation
|
120 |
type: text2text-generation
|
121 |
dataset:
|
122 |
-
name: lmqg/
|
123 |
-
type:
|
124 |
-
args:
|
125 |
metrics:
|
126 |
- name: BLEU4
|
127 |
type: bleu4
|
128 |
-
value:
|
129 |
- name: ROUGE-L
|
130 |
type: rouge-l
|
131 |
-
value: 0.
|
132 |
- name: METEOR
|
133 |
type: meteor
|
134 |
-
value: 0.
|
135 |
- name: BERTScore
|
136 |
type: bertscore
|
137 |
-
value: 0.
|
138 |
- name: MoverScore
|
139 |
type: moverscore
|
140 |
-
value: 0.
|
141 |
- task:
|
142 |
name: Text2text Generation
|
143 |
type: text2text-generation
|
144 |
dataset:
|
145 |
name: lmqg/qg_subjqa
|
146 |
-
type:
|
147 |
-
args:
|
148 |
metrics:
|
149 |
- name: BLEU4
|
150 |
type: bleu4
|
151 |
-
value: 1.
|
152 |
- name: ROUGE-L
|
153 |
type: rouge-l
|
154 |
-
value: 0.
|
155 |
- name: METEOR
|
156 |
type: meteor
|
157 |
-
value: 0.
|
158 |
- name: BERTScore
|
159 |
type: bertscore
|
160 |
-
value: 0.
|
161 |
- name: MoverScore
|
162 |
type: moverscore
|
163 |
-
value: 0.
|
164 |
- task:
|
165 |
name: Text2text Generation
|
166 |
type: text2text-generation
|
167 |
dataset:
|
168 |
name: lmqg/qg_subjqa
|
169 |
-
type:
|
170 |
-
args:
|
171 |
metrics:
|
172 |
- name: BLEU4
|
173 |
type: bleu4
|
174 |
-
value: 0.
|
175 |
- name: ROUGE-L
|
176 |
type: rouge-l
|
177 |
-
value: 0.
|
178 |
- name: METEOR
|
179 |
type: meteor
|
180 |
-
value: 0.
|
181 |
- name: BERTScore
|
182 |
type: bertscore
|
183 |
-
value: 0.
|
184 |
- name: MoverScore
|
185 |
type: moverscore
|
186 |
-
value: 0.
|
187 |
- task:
|
188 |
name: Text2text Generation
|
189 |
type: text2text-generation
|
190 |
dataset:
|
191 |
-
name: lmqg/
|
192 |
-
type:
|
193 |
-
args:
|
194 |
metrics:
|
195 |
- name: BLEU4
|
196 |
type: bleu4
|
197 |
-
value: 0.
|
198 |
- name: ROUGE-L
|
199 |
type: rouge-l
|
200 |
-
value: 0.
|
201 |
- name: METEOR
|
202 |
type: meteor
|
203 |
-
value: 0.
|
204 |
- name: BERTScore
|
205 |
type: bertscore
|
206 |
-
value: 0.
|
207 |
- name: MoverScore
|
208 |
type: moverscore
|
209 |
-
value: 0.
|
210 |
- task:
|
211 |
name: Text2text Generation
|
212 |
type: text2text-generation
|
213 |
dataset:
|
214 |
name: lmqg/qg_subjqa
|
215 |
-
type:
|
216 |
-
args:
|
217 |
metrics:
|
218 |
- name: BLEU4
|
219 |
type: bleu4
|
220 |
-
value:
|
221 |
- name: ROUGE-L
|
222 |
type: rouge-l
|
223 |
-
value: 0.
|
224 |
- name: METEOR
|
225 |
type: meteor
|
226 |
-
value: 0.
|
227 |
- name: BERTScore
|
228 |
type: bertscore
|
229 |
-
value: 0.
|
230 |
- name: MoverScore
|
231 |
type: moverscore
|
232 |
-
value: 0.
|
233 |
- task:
|
234 |
name: Text2text Generation
|
235 |
type: text2text-generation
|
236 |
dataset:
|
237 |
-
name: lmqg/
|
238 |
-
type:
|
239 |
-
args:
|
240 |
metrics:
|
241 |
- name: BLEU4
|
242 |
type: bleu4
|
243 |
-
value: 0.
|
244 |
- name: ROUGE-L
|
245 |
type: rouge-l
|
246 |
-
value: 0.
|
247 |
- name: METEOR
|
248 |
type: meteor
|
249 |
-
value: 0.
|
250 |
- name: BERTScore
|
251 |
type: bertscore
|
252 |
-
value: 0.
|
253 |
- name: MoverScore
|
254 |
type: moverscore
|
255 |
-
value: 0.
|
256 |
- task:
|
257 |
name: Text2text Generation
|
258 |
type: text2text-generation
|
259 |
dataset:
|
260 |
name: lmqg/qg_squadshifts
|
261 |
-
type:
|
262 |
-
args:
|
263 |
metrics:
|
264 |
- name: BLEU4
|
265 |
type: bleu4
|
266 |
-
value: 0.
|
267 |
- name: ROUGE-L
|
268 |
type: rouge-l
|
269 |
-
value: 0.
|
270 |
- name: METEOR
|
271 |
type: meteor
|
272 |
-
value: 0.
|
273 |
- name: BERTScore
|
274 |
type: bertscore
|
275 |
-
value: 0.
|
276 |
- name: MoverScore
|
277 |
type: moverscore
|
278 |
-
value: 0.
|
279 |
---
|
280 |
|
281 |
# Model Card of `lmqg/bart-large-squad`
|
@@ -342,21 +348,28 @@ question = pipe('<hl> Beyonce <hl> further expanded her acting career, starring
|
|
342 |
| [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | default | 0.262 | 0.538 | 0.271 | 0.91 | 0.65 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_squad.default.json) |
|
343 |
|
344 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
345 |
|
346 |
### Out-of-domain Metrics
|
347 |
|
348 |
| Dataset | Type | BLEU4 | ROUGE-L | METEOR | BERTScore | MoverScore | Link |
|
349 |
|:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:|
|
350 |
-
| [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) | reddit | 0.06 | 0.224 | 0.215 | 0.91 | 0.606 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_squadshifts.reddit.json) |
|
351 |
-
| [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) | new_wiki | 0.111 | 0.297 | 0.273 | 0.932 | 0.662 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_squadshifts.new_wiki.json) |
|
352 |
| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | tripadvisor | 0.0 | 0.14 | 0.137 | 0.889 | 0.56 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.tripadvisor.json) |
|
353 |
-
| [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) |
|
354 |
-
| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | restaurants | 0.0 | 0.131 | 0.124 | 0.88 | 0.554 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.restaurants.json) |
|
355 |
-
| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | electronics | 0.009 | 0.16 | 0.153 | 0.878 | 0.563 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.electronics.json) |
|
356 |
| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | books | 0.006 | 0.124 | 0.116 | 0.881 | 0.556 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.books.json) |
|
|
|
357 |
| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | movies | 0.0 | 0.125 | 0.119 | 0.875 | 0.553 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.movies.json) |
|
358 |
| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | grocery | 0.005 | 0.123 | 0.151 | 0.878 | 0.57 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.grocery.json) |
|
359 |
-
| [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) |
|
|
|
|
|
|
|
360 |
|
361 |
|
362 |
## Training hyperparameters
|
|
|
46 |
- name: MoverScore
|
47 |
type: moverscore
|
48 |
value: 0.6499011626820898
|
49 |
+
- name: QAAlignedF1Score (BERTScore)
|
50 |
+
type: qa_aligned_f1_score_bertscore
|
51 |
+
value: 0.9553719665829591
|
52 |
+
- name: QAAlignedF1Score (MoverScore)
|
53 |
+
type: qa_aligned_f1_score_moverscore
|
54 |
+
value: 0.7082452551815105
|
55 |
- task:
|
56 |
name: Text2text Generation
|
57 |
type: text2text-generation
|
58 |
dataset:
|
59 |
+
name: lmqg/qg_subjqa
|
60 |
+
type: tripadvisor
|
61 |
+
args: tripadvisor
|
62 |
metrics:
|
63 |
- name: BLEU4
|
64 |
type: bleu4
|
65 |
+
value: 8.380171318718442e-07
|
66 |
- name: ROUGE-L
|
67 |
type: rouge-l
|
68 |
+
value: 0.1402922852924756
|
69 |
- name: METEOR
|
70 |
type: meteor
|
71 |
+
value: 0.1372146070365174
|
72 |
- name: BERTScore
|
73 |
type: bertscore
|
74 |
+
value: 0.8891002409937424
|
75 |
- name: MoverScore
|
76 |
type: moverscore
|
77 |
+
value: 0.5604572211470809
|
78 |
- task:
|
79 |
name: Text2text Generation
|
80 |
type: text2text-generation
|
81 |
dataset:
|
82 |
name: lmqg/qg_squadshifts
|
83 |
+
type: amazon
|
84 |
+
args: amazon
|
85 |
metrics:
|
86 |
- name: BLEU4
|
87 |
type: bleu4
|
88 |
+
value: 0.06530369842068952
|
89 |
- name: ROUGE-L
|
90 |
type: rouge-l
|
91 |
+
value: 0.25030985091008146
|
92 |
- name: METEOR
|
93 |
type: meteor
|
94 |
+
value: 0.2229994442645732
|
95 |
- name: BERTScore
|
96 |
type: bertscore
|
97 |
+
value: 0.9092814804525936
|
98 |
- name: MoverScore
|
99 |
type: moverscore
|
100 |
+
value: 0.6086538514008419
|
101 |
- task:
|
102 |
name: Text2text Generation
|
103 |
type: text2text-generation
|
104 |
dataset:
|
105 |
name: lmqg/qg_subjqa
|
106 |
+
type: books
|
107 |
+
args: books
|
108 |
metrics:
|
109 |
- name: BLEU4
|
110 |
type: bleu4
|
111 |
+
value: 0.006278914808207679
|
112 |
- name: ROUGE-L
|
113 |
type: rouge-l
|
114 |
+
value: 0.12368226019088967
|
115 |
- name: METEOR
|
116 |
type: meteor
|
117 |
+
value: 0.11576293675813865
|
118 |
- name: BERTScore
|
119 |
type: bertscore
|
120 |
+
value: 0.8807110440044503
|
121 |
- name: MoverScore
|
122 |
type: moverscore
|
123 |
+
value: 0.5555905941686486
|
124 |
- task:
|
125 |
name: Text2text Generation
|
126 |
type: text2text-generation
|
127 |
dataset:
|
128 |
+
name: lmqg/qg_subjqa
|
129 |
+
type: restaurants
|
130 |
+
args: restaurants
|
131 |
metrics:
|
132 |
- name: BLEU4
|
133 |
type: bleu4
|
134 |
+
value: 1.1301750984972448e-06
|
135 |
- name: ROUGE-L
|
136 |
type: rouge-l
|
137 |
+
value: 0.13083168975354642
|
138 |
- name: METEOR
|
139 |
type: meteor
|
140 |
+
value: 0.12419733006916912
|
141 |
- name: BERTScore
|
142 |
type: bertscore
|
143 |
+
value: 0.8797711839570719
|
144 |
- name: MoverScore
|
145 |
type: moverscore
|
146 |
+
value: 0.5542757411268555
|
147 |
- task:
|
148 |
name: Text2text Generation
|
149 |
type: text2text-generation
|
150 |
dataset:
|
151 |
name: lmqg/qg_subjqa
|
152 |
+
type: movies
|
153 |
+
args: movies
|
154 |
metrics:
|
155 |
- name: BLEU4
|
156 |
type: bleu4
|
157 |
+
value: 1.0121579426501661e-06
|
158 |
- name: ROUGE-L
|
159 |
type: rouge-l
|
160 |
+
value: 0.12508697028506718
|
161 |
- name: METEOR
|
162 |
type: meteor
|
163 |
+
value: 0.11862284941640638
|
164 |
- name: BERTScore
|
165 |
type: bertscore
|
166 |
+
value: 0.8748829724726739
|
167 |
- name: MoverScore
|
168 |
type: moverscore
|
169 |
+
value: 0.5528899173535703
|
170 |
- task:
|
171 |
name: Text2text Generation
|
172 |
type: text2text-generation
|
173 |
dataset:
|
174 |
name: lmqg/qg_subjqa
|
175 |
+
type: grocery
|
176 |
+
args: grocery
|
177 |
metrics:
|
178 |
- name: BLEU4
|
179 |
type: bleu4
|
180 |
+
value: 0.00528043272450429
|
181 |
- name: ROUGE-L
|
182 |
type: rouge-l
|
183 |
+
value: 0.12343711316491492
|
184 |
- name: METEOR
|
185 |
type: meteor
|
186 |
+
value: 0.15133496445452477
|
187 |
- name: BERTScore
|
188 |
type: bertscore
|
189 |
+
value: 0.8778951253890991
|
190 |
- name: MoverScore
|
191 |
type: moverscore
|
192 |
+
value: 0.5701949938103265
|
193 |
- task:
|
194 |
name: Text2text Generation
|
195 |
type: text2text-generation
|
196 |
dataset:
|
197 |
+
name: lmqg/qg_squadshifts
|
198 |
+
type: nyt
|
199 |
+
args: nyt
|
200 |
metrics:
|
201 |
- name: BLEU4
|
202 |
type: bleu4
|
203 |
+
value: 0.08117757543966063
|
204 |
- name: ROUGE-L
|
205 |
type: rouge-l
|
206 |
+
value: 0.25292097720734297
|
207 |
- name: METEOR
|
208 |
type: meteor
|
209 |
+
value: 0.25254205113198686
|
210 |
- name: BERTScore
|
211 |
type: bertscore
|
212 |
+
value: 0.9249009759439454
|
213 |
- name: MoverScore
|
214 |
type: moverscore
|
215 |
+
value: 0.6406329128556304
|
216 |
- task:
|
217 |
name: Text2text Generation
|
218 |
type: text2text-generation
|
219 |
dataset:
|
220 |
name: lmqg/qg_subjqa
|
221 |
+
type: electronics
|
222 |
+
args: electronics
|
223 |
metrics:
|
224 |
- name: BLEU4
|
225 |
type: bleu4
|
226 |
+
value: 0.00866799444965211
|
227 |
- name: ROUGE-L
|
228 |
type: rouge-l
|
229 |
+
value: 0.1601628874804186
|
230 |
- name: METEOR
|
231 |
type: meteor
|
232 |
+
value: 0.15348605312210778
|
233 |
- name: BERTScore
|
234 |
type: bertscore
|
235 |
+
value: 0.8783386920680519
|
236 |
- name: MoverScore
|
237 |
type: moverscore
|
238 |
+
value: 0.5634845371093992
|
239 |
- task:
|
240 |
name: Text2text Generation
|
241 |
type: text2text-generation
|
242 |
dataset:
|
243 |
+
name: lmqg/qg_squadshifts
|
244 |
+
type: new_wiki
|
245 |
+
args: new_wiki
|
246 |
metrics:
|
247 |
- name: BLEU4
|
248 |
type: bleu4
|
249 |
+
value: 0.11118273173452982
|
250 |
- name: ROUGE-L
|
251 |
type: rouge-l
|
252 |
+
value: 0.2967546690273089
|
253 |
- name: METEOR
|
254 |
type: meteor
|
255 |
+
value: 0.27315087810722966
|
256 |
- name: BERTScore
|
257 |
type: bertscore
|
258 |
+
value: 0.9322739617807421
|
259 |
- name: MoverScore
|
260 |
type: moverscore
|
261 |
+
value: 0.6623000084761579
|
262 |
- task:
|
263 |
name: Text2text Generation
|
264 |
type: text2text-generation
|
265 |
dataset:
|
266 |
name: lmqg/qg_squadshifts
|
267 |
+
type: reddit
|
268 |
+
args: reddit
|
269 |
metrics:
|
270 |
- name: BLEU4
|
271 |
type: bleu4
|
272 |
+
value: 0.059525104157825456
|
273 |
- name: ROUGE-L
|
274 |
type: rouge-l
|
275 |
+
value: 0.22365090580055863
|
276 |
- name: METEOR
|
277 |
type: meteor
|
278 |
+
value: 0.21499800504546457
|
279 |
- name: BERTScore
|
280 |
type: bertscore
|
281 |
+
value: 0.9095144685254328
|
282 |
- name: MoverScore
|
283 |
type: moverscore
|
284 |
+
value: 0.6059332247878408
|
285 |
---
|
286 |
|
287 |
# Model Card of `lmqg/bart-large-squad`
|
|
|
348 |
| [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | default | 0.262 | 0.538 | 0.271 | 0.91 | 0.65 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_squad.default.json) |
|
349 |
|
350 |
|
351 |
+
### Metrics (QAG)
|
352 |
+
|
353 |
+
| Dataset | Type | QA Aligned F1 Score (BERTScore) | QA Aligned F1 Score (MoverScore) | Link |
|
354 |
+
|:--------|:-----|--------------------------------:|---------------------------------:|-----:|
|
355 |
+
| [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | default | 0.955 | 0.708 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval/metric.first.answer.paragraph.questions_answers.lmqg_qg_squad.default.json) |
|
356 |
+
|
357 |
+
|
358 |
|
359 |
### Out-of-domain Metrics
|
360 |
|
361 |
| Dataset | Type | BLEU4 | ROUGE-L | METEOR | BERTScore | MoverScore | Link |
|
362 |
|:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:|
|
|
|
|
|
363 |
| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | tripadvisor | 0.0 | 0.14 | 0.137 | 0.889 | 0.56 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.tripadvisor.json) |
|
364 |
+
| [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) | amazon | 0.065 | 0.25 | 0.223 | 0.909 | 0.609 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_squadshifts.amazon.json) |
|
|
|
|
|
365 |
| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | books | 0.006 | 0.124 | 0.116 | 0.881 | 0.556 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.books.json) |
|
366 |
+
| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | restaurants | 0.0 | 0.131 | 0.124 | 0.88 | 0.554 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.restaurants.json) |
|
367 |
| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | movies | 0.0 | 0.125 | 0.119 | 0.875 | 0.553 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.movies.json) |
|
368 |
| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | grocery | 0.005 | 0.123 | 0.151 | 0.878 | 0.57 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.grocery.json) |
|
369 |
+
| [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) | nyt | 0.081 | 0.253 | 0.253 | 0.925 | 0.641 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_squadshifts.nyt.json) |
|
370 |
+
| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | electronics | 0.009 | 0.16 | 0.153 | 0.878 | 0.563 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.electronics.json) |
|
371 |
+
| [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) | new_wiki | 0.111 | 0.297 | 0.273 | 0.932 | 0.662 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_squadshifts.new_wiki.json) |
|
372 |
+
| [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) | reddit | 0.06 | 0.224 | 0.215 | 0.91 | 0.606 | [link](https://huggingface.co/lmqg/bart-large-squad/raw/main/eval_ood/metric.first.sentence.paragraph_answer.question.lmqg_qg_squadshifts.reddit.json) |
|
373 |
|
374 |
|
375 |
## Training hyperparameters
|