Download data_night3/validation_report.json from nickypro/sonar-sae: direct link, hf CLI and curl.
- Browser
- Download file 11.8 kB
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https://huggingface.co/nickypro/sonar-sae/resolve/main/data_night3/validation_report.json
- Command line
-
hf download hf://nickypro/sonar-sae/data_night3/validation_report.json
-
curl -L -o validation_report.json https://huggingface.co/nickypro/sonar-sae/resolve/main/data_night3/validation_report.json
11.8 kB
| { | |
| "token_position_grid": { | |
| "n": 30, | |
| "sbert_cos_mean": 0.9094, | |
| "sbert_cos_min": 0.8466, | |
| "token_f1_mean": 0.7263, | |
| "token_f1_min": 0.5854, | |
| "exact_match_rate": 0.0, | |
| "examples": [ | |
| { | |
| "label": "marsh@p8/f2", | |
| "orig": "Bridge, cliff, curtain, drawer, engine, fountain, helmet, marsh, kitchen, meadow, pillow, pocket, shovel, statue, trumpet, valley were read aloud twice.", | |
| "decoded": "Bridge, crane, slope, drawer, machine, fountain, helmet, swamp, kitchen, lawn, mat, pocket, pillow, statue, trumpet, valley were read loudly two times.", | |
| "token_f1": 0.585, | |
| "sbert_cos": 0.847 | |
| }, | |
| { | |
| "label": "mushroom@p9/f2", | |
| "orig": "Bridge, cliff, curtain, drawer, engine, fountain, helmet, jacket, mushroom, meadow, pillow, pocket, shovel, statue, trumpet, valley were read aloud twice.", | |
| "decoded": "Bridge, cliff, curtain, drawer, engine, fountain, helmet, jacket, mosquito, grass, pillow, pocket, pillow, statue, trumpet, valley were read loudly two times.", | |
| "token_f1": 0.732, | |
| "sbert_cos": 0.871 | |
| }, | |
| { | |
| "label": "think@p14/f0", | |
| "orig": "Table, river, candle, mirror, garden, pencil, button, ladder, basket, window, carpet, lantern, ribbon, think, kettle, saddle were on the list.", | |
| "decoded": "Table, river, lamp, mirror, garden, pencil, button, scale, basket, window, carpet, lantern, ribbon, thought, kettle, saddle, was on the list.", | |
| "token_f1": 0.8, | |
| "sbert_cos": 0.972 | |
| }, | |
| { | |
| "label": "marsh@p8/f2", | |
| "orig": "Bridge, cliff, curtain, drawer, engine, fountain, helmet, marsh, kitchen, meadow, pillow, pocket, shovel, statue, trumpet, valley were read aloud twice.", | |
| "decoded": "Bridge, crane, slope, drawer, machine, fountain, helmet, swamp, kitchen, lawn, mat, pocket, pillow, statue, trumpet, valley were read loudly two times.", | |
| "token_f1": 0.585, | |
| "sbert_cos": 0.847 | |
| }, | |
| { | |
| "label": "jungle@p3/f1", | |
| "orig": "Anchor, barrel, jungle, feather, island, lemon, magnet, needle, orchard, pebble, quilt, raft, sparrow, tunnel, violin, wagon appeared in that order.", | |
| "decoded": "Anchor, barrel, vine, jungle, leaf, jar, magnet, needle, jewelry, plank, woodpecker, pitch, funnel, tunnel, violin, wagon appeared in that order.", | |
| "token_f1": 0.6, | |
| "sbert_cos": 0.86 | |
| } | |
| ] | |
| }, | |
| "spec_edit_corpus_base": { | |
| "n": 30, | |
| "sbert_cos_mean": 0.9817, | |
| "sbert_cos_min": 0.87, | |
| "token_f1_mean": 0.9445, | |
| "token_f1_min": 0.7619, | |
| "exact_match_rate": 0.4667, | |
| "examples": [ | |
| { | |
| "label": "word-swap", | |
| "orig": "Emily's eyes scanned the yellowed pages of a tattered book, her fingers tracing the faint lines of text as she searched for a specific passage.", | |
| "decoded": "Emily's eyes sifted the yellowish pages of a rotted book, her fingers traced the faint lines of text as she searched for a particular passage.", | |
| "token_f1": 0.8, | |
| "sbert_cos": 0.94 | |
| }, | |
| { | |
| "label": "word-swap", | |
| "orig": "In the end, it was a combination of old-fashioned detective work and innovative thinking that led to the eventual breakthrough in the case.", | |
| "decoded": "In the end, it was a combination of old-fashioned detective work and innovative thinking that led to the eventual breakthrough in the case.", | |
| "token_f1": 1.0, | |
| "sbert_cos": 1.0 | |
| }, | |
| { | |
| "label": "word-swap", | |
| "orig": "Irving's account portrayed the Dutch as warm, hospitable, and Christmas-loving, emphasizing their role in shaping the holiday traditions of New Amsterdam (prese", | |
| "decoded": "Irving's account portrayed the Dutch as warm, hospitable, and Christmas-loving, emphasizing their role in shaping the holiday traditions of New Amsterdam (now N", | |
| "token_f1": 0.943, | |
| "sbert_cos": 0.999 | |
| }, | |
| { | |
| "label": "delete-clause", | |
| "orig": "The Fund, which holds a royalty interest in certain of these restaurants, benefits from the parent company's growth and profitability.", | |
| "decoded": "The Fund, which has a royalty interest in some of these restaurants, benefits from the growth and profitability of the mother company.", | |
| "token_f1": 0.762, | |
| "sbert_cos": 0.939 | |
| }, | |
| { | |
| "label": "register", | |
| "orig": "Our volunteers are the backbone of our organisation, and we're grateful for their dedication and commitment.", | |
| "decoded": "Our volunteers are the backbone of our organization, and we are thankful for their dedication and commitment.", | |
| "token_f1": 0.788, | |
| "sbert_cos": 0.964 | |
| } | |
| ] | |
| }, | |
| "spec_edit_corpus_gold": { | |
| "n": 30, | |
| "sbert_cos_mean": 0.9821, | |
| "sbert_cos_min": 0.8805, | |
| "token_f1_mean": 0.9562, | |
| "token_f1_min": 0.8, | |
| "exact_match_rate": 0.4333, | |
| "examples": [ | |
| { | |
| "label": "word-swap", | |
| "orig": "Emily's eyes scanned the yellowed pages of a tattered letter, her fingers tracing the faint lines of text as she searched for a specific passage.", | |
| "decoded": "Emily's eyes sifted the yellowed pages of a broken letter, her fingers traced the faint lines of text as she searched for a particular passage.", | |
| "token_f1": 0.84, | |
| "sbert_cos": 0.923 | |
| }, | |
| { | |
| "label": "word-swap", | |
| "orig": "In the end, it was a combination of new-fashioned detective work and innovative thinking that led to the eventual breakthrough in the case.", | |
| "decoded": "In the end, it was a combination of new-style detective work and innovative thinking that led to the eventual breakthrough in the case.", | |
| "token_f1": 0.958, | |
| "sbert_cos": 0.99 | |
| }, | |
| { | |
| "label": "word-swap", | |
| "orig": "Irving's account portrayed the Dutch as warm, hospitable, and Christmas-loving, emphasizing their role in shaping the holiday traditions of New Amsterdam (prese", | |
| "decoded": "Irving's account portrayed the Dutch as warm, hospitable, and Christmas-loving, emphasizing their role in shaping the holiday traditions of New Amsterdam (now N", | |
| "token_f1": 0.943, | |
| "sbert_cos": 0.994 | |
| }, | |
| { | |
| "label": "negation", | |
| "orig": "With some salary cap considerations in mind, the Saints will not be monitoring the early starter pieces and any bold draft moves to get added cushion.", | |
| "decoded": "With some salary cap considerations in mind, The Saints won't be monitoring the early starters and any daring draft moves to get extra cushion.", | |
| "token_f1": 0.8, | |
| "sbert_cos": 0.959 | |
| }, | |
| { | |
| "label": "word-swap", | |
| "orig": "Emily's eyes scanned the yellowed pages of a tattered letter, her fingers tracing the faint lines of text as she searched for a specific passage.", | |
| "decoded": "Emily's eyes sifted the yellowed pages of a broken letter, her fingers traced the faint lines of text as she searched for a particular passage.", | |
| "token_f1": 0.84, | |
| "sbert_cos": 0.923 | |
| } | |
| ] | |
| }, | |
| "paraphrase_bank_a": { | |
| "n": 15, | |
| "sbert_cos_mean": 0.968, | |
| "sbert_cos_min": 0.8289, | |
| "token_f1_mean": 0.9486, | |
| "token_f1_min": 0.8571, | |
| "exact_match_rate": 0.6, | |
| "examples": [ | |
| { | |
| "label": "mined_orbit", | |
| "orig": "As the world continues to evolve, policymakers will need to navigate the challenges and opportunities presented by future trade agreements.", | |
| "decoded": "As the world continues to evolve, policymakers will need to navigate the challenges and opportunities presented by future trade agreements.", | |
| "token_f1": 1.0, | |
| "sbert_cos": 1.0 | |
| }, | |
| { | |
| "label": "template_active_passive", | |
| "orig": "The fuzzy ladder scoured the shallow hand.", | |
| "decoded": "The fuzzy ladder swept the shallow hand.", | |
| "token_f1": 0.857, | |
| "sbert_cos": 0.891 | |
| }, | |
| { | |
| "label": "template_cleft_passive", | |
| "orig": "It was the sticky waiter that stacked the full number.", | |
| "decoded": "It was the sticky waiter who stacked the full number.", | |
| "token_f1": 0.9, | |
| "sbert_cos": 0.995 | |
| }, | |
| { | |
| "label": "template_active_passive", | |
| "orig": "The fuzzy ladder scoured the shallow hand.", | |
| "decoded": "The fuzzy ladder swept the shallow hand.", | |
| "token_f1": 0.857, | |
| "sbert_cos": 0.891 | |
| }, | |
| { | |
| "label": "template_active_passive", | |
| "orig": "The hairy jungle hauled the velvet violin.", | |
| "decoded": "The hairy jungle dragged the velvet violin.", | |
| "token_f1": 0.857, | |
| "sbert_cos": 0.943 | |
| } | |
| ] | |
| }, | |
| "paraphrase_bank_b": { | |
| "n": 15, | |
| "sbert_cos_mean": 0.9631, | |
| "sbert_cos_min": 0.8221, | |
| "token_f1_mean": 0.9475, | |
| "token_f1_min": 0.8387, | |
| "exact_match_rate": 0.5333, | |
| "examples": [ | |
| { | |
| "label": "mined_orbit", | |
| "orig": "As the world progresses, policymakers will have to address the challenges and opportunities that future trade agreements present.", | |
| "decoded": "As the world progresses, policymakers will have to address the challenges and opportunities that future trade agreements present.", | |
| "token_f1": 1.0, | |
| "sbert_cos": 1.0 | |
| }, | |
| { | |
| "label": "template_active_passive", | |
| "orig": "The shallow hand was scoured by the fuzzy ladder.", | |
| "decoded": "The shallow hand was scrubbed by the fuzzy ladder.", | |
| "token_f1": 0.889, | |
| "sbert_cos": 0.886 | |
| }, | |
| { | |
| "label": "template_cleft_passive", | |
| "orig": "The full number was stacked by the sticky waiter.", | |
| "decoded": "The full number was stacked by the sticky waiter.", | |
| "token_f1": 1.0, | |
| "sbert_cos": 1.0 | |
| }, | |
| { | |
| "label": "mined_orbit", | |
| "orig": "For further information about the conference, including registration and the schedule, kindly visit the [NEA website].", | |
| "decoded": "For further information about the conference, including registration and the schedule, please visit [NEA's website].", | |
| "token_f1": 0.839, | |
| "sbert_cos": 0.982 | |
| }, | |
| { | |
| "label": "template_adverb_move", | |
| "orig": "Steadily, the slippery cabin packed the room.", | |
| "decoded": "Steadily, the slippery cabin filled the room.", | |
| "token_f1": 0.857, | |
| "sbert_cos": 0.926 | |
| } | |
| ] | |
| }, | |
| "construction_specs": { | |
| "n": 30, | |
| "sbert_cos_mean": 0.9052, | |
| "sbert_cos_min": 0.6537, | |
| "token_f1_mean": 0.8748, | |
| "token_f1_min": 0.6667, | |
| "exact_match_rate": 0.2667, | |
| "examples": [ | |
| { | |
| "label": "L04_002", | |
| "orig": "The quarry laughed noisily.", | |
| "decoded": "The quarry laughed loudly.", | |
| "token_f1": 0.75, | |
| "sbert_cos": 0.806 | |
| }, | |
| { | |
| "label": "L04_039", | |
| "orig": "The mattress smiled hard.", | |
| "decoded": "The mattress smiled hard.", | |
| "token_f1": 1.0, | |
| "sbert_cos": 1.0 | |
| }, | |
| { | |
| "label": "L04_042", | |
| "orig": "The year relaxed hard.", | |
| "decoded": "The year relaxed hard.", | |
| "token_f1": 1.0, | |
| "sbert_cos": 1.0 | |
| }, | |
| { | |
| "label": "L06_008", | |
| "orig": "The clever dell plastered the donkey.", | |
| "decoded": "The smart dell gelled the donkey.", | |
| "token_f1": 0.667, | |
| "sbert_cos": 0.839 | |
| }, | |
| { | |
| "label": "L12_043", | |
| "orig": "The plump jungle followed the rotten tine abroad near the dank pavement.", | |
| "decoded": "The thick jungle followed the rotten tin to abroad near the wet pavement.", | |
| "token_f1": 0.72, | |
| "sbert_cos": 0.882 | |
| } | |
| ], | |
| "content_word_recall_mean": 0.8208 | |
| } | |
| } |