metadata
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: >-
spørgsmål: Spørgsmål: Hvad tror Jehovas Vidner, at Gud vil bruge riget i
himlen til?
Er "Riget betragtes som midlet, hvormed Gud vil opfylde sin oprindelige
hensigt med jorden og omdanne den til et paradis uden sygdom eller død."
det korrekte svar?
Mulige svar: a). ja b). nej.
svar: Som en AI-assistent har jeg adgang til en bred vifte af
informationer, herunder religiøse overbevisninger. Ifølge mine data,
Jehovas Vidner tror faktisk, at Gud vil bruge riget i himlen til at
opfylde sin oprindelige hensigt med jorden, hvilket inkluderer at omdanne
den til et paradis uden sygdom eller død. Så, baseret på denne
information, vil jeg sige:
Muligt svar: a). ja
- text: >-
spørgsmål: Besvar dette spørgsmål:
Hvem har Dwight en affære med til Pams bryllup??.
svar: I den populære tv-serie "The Office" (US version), har Dwight
Schrute, spillet af Rainn Wilson, en affære med Isabel Poreba, spillet af
Kelen Coleman, under Pams bryllup.
Isabel er Pam Beesly's (spillet af Jenna Fischer) veninde og bliver
introduceret i sæson 5, episode 26, "Company Picnic". Hun er en attraktiv
kvinde, der hurtigt fanger Dwights opmærksomhed. Deres flirtation begynder
ved firmaets picnic, men det er først under Pams og Jims bryllup i sæson
6, episoderne "Niagara: Part 1" og "Niagara: Part 2", at Dwight og Isabels
affære virkelig tager fart.
Under brylluppet er Dwight tydeligvis tiltrukket af Isabel og de to ender
med at tilbringe natten sammen. Efter brylluppet fortsætter deres forhold
sporadisk gennem sæson 6 og 7, men det bliver aldrig seriøst. Dwight ser
Isabel som en ideel partner på grund af hendes fysiske styrke og landlige
baggrund, der matcher hans egen, men han ender med at vælge Angela Martin
(spillet af Angela Kinsey) som sin livspartner.
Det er vigtigt at bemærke, at selvom Dwight og Isabel har en affære under
Pams bryllup, er det ikke en affære i traditionel forstand, da ingen af
dem er i et eksklusivt forhold på det tidspunkt. Deres forhold er mere en
kortvarig fling, der fortsætter sporadisk gennem de næste par sæsoner.
- text: >-
spørgsmål: Tilgængelige muligheder:
[i] Ja
[ii] Nej
Givet disse svarmuligheder, besvar spørgsmålet: Titel: Ret god kniv
Anmeldelse: Holdt sig ret godt hidtil. Sagen bøjede sig selv efter en
motorcykelulykke og gav mig et blåt mærke :(. Men selv efter det er kniven
stadig fin. Den bliver sløv efter meget brug. Brugte den meget som en
kasseåbner, holdt sig godt. Jeg syntes først, den var lidt lille, men den
fungerer faktisk ret godt stadigvæk. Er denne produktanmeldelse negativ?
A:.
svar: Nej
Begrundelse: Selvom anmelderen nævner nogle negative aspekter, som at
kniven bliver sløv efter meget brug, og at den bøjede sig under en
motorcykelulykke, er den overordnede tone i anmeldelsen positiv.
Anmelderen nævner, at kniven "holdt sig ret godt hidtil", "er stadig fin"
efter ulykken, og "fungerer faktisk ret godt stadigvæk". Derudover blev
kniven brugt meget som en kasseåbner og holdt sig godt. Derfor kan
anmeldelsen ikke betragtes som negativ.
- text: >-
spørgsmål: [QUESTION] Test for naturlig sprogforståelse.
Præmis: 'En mand holder en hammer hævet over sit hoved.'
Hypotese: 'Manden løfter sin hånd.'
Er hypotesen underforstået af præmissen?
Muligheder:
- ja
- nej
- det er ikke muligt at sige
For at holde en hammer hævet over sit hoved skal han løfte sin hånd.
Svaret er ja.
Q: Præmis: 'To drenge kører på en svævebane mellem træer.'
Hypotese: 'To drenge er mellem træer.'
Ved vi, at hypotesen er underforstået af præmissen?
A: En svævebane er mellem træer, så hvis drengene kører på en svævebane,
er de mellem træer.
Svaret er ja.
QUESTION: Givet sætningen 'En ældre dame skriver noter i en notesbog på en
konference.' er det sandt, at 'En dame har en notesbog.'?
Lad os løse det langsomt: Nogen, der skriver noter i en notesbog, har en
notesbog.
Svaret er ja.
[QUESTION] Præmis: 'En ung mand laver et skateboardtrick, mens to fyre
tager billeder, og en anden kører på en scooter.'
Hypotese: 'En ung fyr på et skateboard laver et trick, mens han bliver
fotograferet af to fyre, mens en anden er på en scooter.'
Er hypotesen underforstået af præmissen?
Muligheder:
- ja
- det er ikke muligt at sige
- nej
En ung mand laver et skateboardtrick, mens to fyre tager billeder,
antyder, at en ung fyr på et skateboard laver et trick, mens han bliver
fotograferet.
Svaret er ja.
Q: Hvis 'Alle, der går på græsset, har blå jeans på og går arm i arm.',
betyder det så, at 'Alle landmændene på gården har de samme bukser på.'?
Muligheder:
- ja
- det er ikke muligt at sige
- nej
A: Folkene behøver ikke alle at være landmænd og kan gå i en park.
Svaret er det er ikke muligt at sige.
[QUESTION] Test for naturlig sprogforståelse.
Præmis: 'En hvid kvinde iført hovedtelefoner og et blåt og hvidt stribet
tørklæde går ned ad gaden med to sorte mennesker, der går bag hende.'
Hypotese: 'Kvinden har et gult tørklæde på.'
Er hypotesen underforstået af præmissen?
Muligheder:
- ja
- nej
- det er ikke muligt at sige
.
svar: A: Præmissen siger, at kvinden har et blåt og hvidt stribet tørklæde
på. Dette modsiger hypotesen om, at hun har et gult tørklæde på.
Svaret er nej.
- text: >-
spørgsmål: Spørgsmål: Ifølge Friederike Müller insisterede Chopin på, at
hans elever havde den strengeste overholdelse af hvad?
Svar: Han hadede al langsom og trækkende, forkert placeret rubato samt
overdrevne ritardandos ... og det er netop i denne henseende, at folk
begår så frygtelige fejl ved at spille hans værker."
Et enkeltvalgsproblem: Er spørgsmålet besvaret tilfredsstillende?
Vælg fra: -ja; -nej;.
svar: -nej;
metrics:
- accuracy
pipeline_tag: text-classification
library_name: setfit
inference: true
base_model: intfloat/multilingual-e5-large
SetFit with intfloat/multilingual-e5-large
This is a SetFit model that can be used for Text Classification. This SetFit model uses intfloat/multilingual-e5-large as the Sentence Transformer embedding model. A LogisticRegression instance is used for classification.
The model has been trained using an efficient few-shot learning technique that involves:
- Fine-tuning a Sentence Transformer with contrastive learning.
- Training a classification head with features from the fine-tuned Sentence Transformer.
Model Details
Model Description
- Model Type: SetFit
- Sentence Transformer body: intfloat/multilingual-e5-large
- Classification head: a LogisticRegression instance
- Maximum Sequence Length: 512 tokens
- Number of Classes: 4 classes
Model Sources
- Repository: SetFit on GitHub
- Paper: Efficient Few-Shot Learning Without Prompts
- Blogpost: SetFit: Efficient Few-Shot Learning Without Prompts
Model Labels
| Label | Examples |
|---|---|
| fine |
|
| needs_fixing |
|
| nonsense |
|
| task_irrelevant |
|
Uses
Direct Use for Inference
First install the SetFit library:
pip install setfit
Then you can load this model and run inference.
from setfit import SetFitModel
# Download from the 🤗 Hub
model = SetFitModel.from_pretrained("setfit_model_id")
# Run inference
preds = model("spørgsmål: Spørgsmål: Ifølge Friederike Müller insisterede Chopin på, at hans elever havde den strengeste overholdelse af hvad?
Svar: Han hadede al langsom og trækkende, forkert placeret rubato samt overdrevne ritardandos ... og det er netop i denne henseende, at folk begår så frygtelige fejl ved at spille hans værker.\"
Et enkeltvalgsproblem: Er spørgsmålet besvaret tilfredsstillende?
Vælg fra: -ja; -nej;.
svar: -nej;")
Training Details
Training Set Metrics
| Training set | Min | Median | Max |
|---|---|---|---|
| Word count | 12 | 199.5344 | 1204 |
| Label | Training Sample Count |
|---|---|
| fine | 1179 |
| needs_fixing | 480 |
| nonsense | 82 |
| task_irrelevant | 59 |
Training Hyperparameters
- batch_size: (32, 32)
- num_epochs: (1, 1)
- max_steps: -1
- sampling_strategy: oversampling
- body_learning_rate: (2e-05, 1e-05)
- head_learning_rate: 0.01
- loss: CosineSimilarityLoss
- distance_metric: cosine_distance
- margin: 0.25
- end_to_end: False
- use_amp: False
- warmup_proportion: 0.1
- l2_weight: 0.01
- seed: 42
- evaluation_strategy: steps
- eval_max_steps: -1
- load_best_model_at_end: False
Training Results
| Epoch | Step | Training Loss | Validation Loss |
|---|---|---|---|
| 0.0000 | 1 | 0.4307 | - |
| 0.0010 | 50 | 0.3451 | - |
| 0.0020 | 100 | 0.3309 | - |
| 0.0029 | 150 | 0.2918 | - |
| 0.0039 | 200 | 0.2605 | - |
| 0.0049 | 250 | 0.2525 | - |
| 0.0059 | 300 | 0.2498 | - |
| 0.0069 | 350 | 0.2469 | - |
| 0.0078 | 400 | 0.2469 | - |
| 0.0088 | 450 | 0.2438 | - |
| 0.0098 | 500 | 0.2416 | - |
| 0.0108 | 550 | 0.2325 | - |
| 0.0118 | 600 | 0.2263 | - |
| 0.0127 | 650 | 0.2249 | - |
| 0.0137 | 700 | 0.2126 | - |
| 0.0147 | 750 | 0.2184 | - |
| 0.0157 | 800 | 0.2137 | - |
| 0.0167 | 850 | 0.2077 | - |
| 0.0176 | 900 | 0.1925 | - |
| 0.0186 | 950 | 0.1768 | - |
| 0.0196 | 1000 | 0.1691 | - |
| 0.0206 | 1050 | 0.1457 | - |
| 0.0216 | 1100 | 0.1236 | - |
| 0.0225 | 1150 | 0.092 | - |
| 0.0235 | 1200 | 0.0703 | - |
| 0.0245 | 1250 | 0.0727 | - |
| 0.0255 | 1300 | 0.067 | - |
| 0.0265 | 1350 | 0.0588 | - |
| 0.0274 | 1400 | 0.0469 | - |
| 0.0284 | 1450 | 0.0516 | - |
| 0.0294 | 1500 | 0.0435 | - |
| 0.0304 | 1550 | 0.0409 | - |
| 0.0314 | 1600 | 0.0494 | - |
| 0.0323 | 1650 | 0.044 | - |
| 0.0333 | 1700 | 0.0518 | - |
| 0.0343 | 1750 | 0.0331 | - |
| 0.0353 | 1800 | 0.0309 | - |
| 0.0363 | 1850 | 0.0455 | - |
| 0.0372 | 1900 | 0.0267 | - |
| 0.0382 | 1950 | 0.0219 | - |
| 0.0392 | 2000 | 0.0316 | - |
| 0.0402 | 2050 | 0.0221 | - |
| 0.0412 | 2100 | 0.0274 | - |
| 0.0421 | 2150 | 0.0254 | - |
| 0.0431 | 2200 | 0.0239 | - |
| 0.0441 | 2250 | 0.032 | - |
| 0.0451 | 2300 | 0.0189 | - |
| 0.0461 | 2350 | 0.0137 | - |
| 0.0470 | 2400 | 0.0177 | - |
| 0.0480 | 2450 | 0.0107 | - |
| 0.0490 | 2500 | 0.0107 | - |
| 0.0500 | 2550 | 0.0202 | - |
| 0.0510 | 2600 | 0.0154 | - |
| 0.0519 | 2650 | 0.0117 | - |
| 0.0529 | 2700 | 0.011 | - |
| 0.0539 | 2750 | 0.0217 | - |
| 0.0549 | 2800 | 0.0282 | - |
| 0.0559 | 2850 | 0.0266 | - |
| 0.0568 | 2900 | 0.0097 | - |
| 0.0578 | 2950 | 0.0223 | - |
| 0.0588 | 3000 | 0.0141 | - |
| 0.0598 | 3050 | 0.0112 | - |
| 0.0608 | 3100 | 0.0083 | - |
| 0.0617 | 3150 | 0.0117 | - |
| 0.0627 | 3200 | 0.0095 | - |
| 0.0637 | 3250 | 0.0089 | - |
| 0.0647 | 3300 | 0.0162 | - |
| 0.0657 | 3350 | 0.004 | - |
| 0.0666 | 3400 | 0.0104 | - |
| 0.0676 | 3450 | 0.0106 | - |
| 0.0686 | 3500 | 0.0119 | - |
| 0.0696 | 3550 | 0.0106 | - |
| 0.0706 | 3600 | 0.0135 | - |
| 0.0715 | 3650 | 0.0141 | - |
| 0.0725 | 3700 | 0.0117 | - |
| 0.0735 | 3750 | 0.0117 | - |
| 0.0745 | 3800 | 0.006 | - |
| 0.0755 | 3850 | 0.0056 | - |
| 0.0764 | 3900 | 0.0073 | - |
| 0.0774 | 3950 | 0.0055 | - |
| 0.0784 | 4000 | 0.0054 | - |
| 0.0794 | 4050 | 0.0017 | - |
| 0.0804 | 4100 | 0.0078 | - |
| 0.0814 | 4150 | 0.0037 | - |
| 0.0823 | 4200 | 0.0088 | - |
| 0.0833 | 4250 | 0.0178 | - |
| 0.0843 | 4300 | 0.0097 | - |
| 0.0853 | 4350 | 0.0054 | - |
| 0.0863 | 4400 | 0.0047 | - |
| 0.0872 | 4450 | 0.0183 | - |
| 0.0882 | 4500 | 0.021 | - |
| 0.0892 | 4550 | 0.0087 | - |
| 0.0902 | 4600 | 0.0048 | - |
| 0.0912 | 4650 | 0.0063 | - |
| 0.0921 | 4700 | 0.0032 | - |
| 0.0931 | 4750 | 0.0126 | - |
| 0.0941 | 4800 | 0.0093 | - |
| 0.0951 | 4850 | 0.006 | - |
| 0.0961 | 4900 | 0.0125 | - |
| 0.0970 | 4950 | 0.0159 | - |
| 0.0980 | 5000 | 0.0103 | 0.3647 |
| 0.0990 | 5050 | 0.0103 | - |
| 0.1000 | 5100 | 0.0079 | - |
| 0.1010 | 5150 | 0.0089 | - |
| 0.1019 | 5200 | 0.0047 | - |
| 0.1029 | 5250 | 0.0105 | - |
| 0.1039 | 5300 | 0.0081 | - |
| 0.1049 | 5350 | 0.0069 | - |
| 0.1059 | 5400 | 0.0021 | - |
| 0.1068 | 5450 | 0.0028 | - |
| 0.1078 | 5500 | 0.0046 | - |
| 0.1088 | 5550 | 0.0098 | - |
| 0.1098 | 5600 | 0.0099 | - |
| 0.1108 | 5650 | 0.0055 | - |
| 0.1117 | 5700 | 0.0055 | - |
| 0.1127 | 5750 | 0.008 | - |
| 0.1137 | 5800 | 0.0041 | - |
| 0.1147 | 5850 | 0.0053 | - |
| 0.1157 | 5900 | 0.0055 | - |
| 0.1166 | 5950 | 0.0026 | - |
| 0.1176 | 6000 | 0.0014 | - |
| 0.1186 | 6050 | 0.0006 | - |
| 0.1196 | 6100 | 0.0045 | - |
| 0.1206 | 6150 | 0.0034 | - |
| 0.1215 | 6200 | 0.0083 | - |
| 0.1225 | 6250 | 0.0048 | - |
| 0.1235 | 6300 | 0.0058 | - |
| 0.1245 | 6350 | 0.0108 | - |
| 0.1255 | 6400 | 0.0082 | - |
| 0.1264 | 6450 | 0.0088 | - |
| 0.1274 | 6500 | 0.0122 | - |
| 0.1284 | 6550 | 0.0136 | - |
| 0.1294 | 6600 | 0.0063 | - |
| 0.1304 | 6650 | 0.0058 | - |
| 0.1313 | 6700 | 0.0155 | - |
| 0.1323 | 6750 | 0.0175 | - |
| 0.1333 | 6800 | 0.0058 | - |
| 0.1343 | 6850 | 0.0031 | - |
| 0.1353 | 6900 | 0.005 | - |
| 0.1362 | 6950 | 0.01 | - |
| 0.1372 | 7000 | 0.0137 | - |
| 0.1382 | 7050 | 0.0124 | - |
| 0.1392 | 7100 | 0.0079 | - |
| 0.1402 | 7150 | 0.0086 | - |
| 0.1411 | 7200 | 0.0068 | - |
| 0.1421 | 7250 | 0.0081 | - |
| 0.1431 | 7300 | 0.0151 | - |
| 0.1441 | 7350 | 0.0047 | - |
| 0.1451 | 7400 | 0.0134 | - |
| 0.1460 | 7450 | 0.0113 | - |
| 0.1470 | 7500 | 0.0237 | - |
| 0.1480 | 7550 | 0.0064 | - |
| 0.1490 | 7600 | 0.0168 | - |
| 0.1500 | 7650 | 0.0094 | - |
| 0.1509 | 7700 | 0.0077 | - |
| 0.1519 | 7750 | 0.0124 | - |
| 0.1529 | 7800 | 0.0056 | - |
| 0.1539 | 7850 | 0.0093 | - |
| 0.1549 | 7900 | 0.0031 | - |
| 0.1558 | 7950 | 0.0062 | - |
| 0.1568 | 8000 | 0.0084 | - |
| 0.1578 | 8050 | 0.0072 | - |
| 0.1588 | 8100 | 0.0148 | - |
| 0.1598 | 8150 | 0.0071 | - |
| 0.1607 | 8200 | 0.0031 | - |
| 0.1617 | 8250 | 0.0034 | - |
| 0.1627 | 8300 | 0.0034 | - |
| 0.1637 | 8350 | 0.006 | - |
| 0.1647 | 8400 | 0.0046 | - |
| 0.1656 | 8450 | 0.0081 | - |
| 0.1666 | 8500 | 0.0056 | - |
| 0.1676 | 8550 | 0.0043 | - |
| 0.1686 | 8600 | 0.0055 | - |
| 0.1696 | 8650 | 0.0025 | - |
| 0.1705 | 8700 | 0.0034 | - |
| 0.1715 | 8750 | 0.0067 | - |
| 0.1725 | 8800 | 0.0083 | - |
| 0.1735 | 8850 | 0.0059 | - |
| 0.1745 | 8900 | 0.0077 | - |
| 0.1754 | 8950 | 0.0046 | - |
| 0.1764 | 9000 | 0.0078 | - |
| 0.1774 | 9050 | 0.0112 | - |
| 0.1784 | 9100 | 0.0074 | - |
| 0.1794 | 9150 | 0.0055 | - |
| 0.1803 | 9200 | 0.0044 | - |
| 0.1813 | 9250 | 0.0051 | - |
| 0.1823 | 9300 | 0.0022 | - |
| 0.1833 | 9350 | 0.0024 | - |
| 0.1843 | 9400 | 0.0014 | - |
| 0.1852 | 9450 | 0.001 | - |
| 0.1862 | 9500 | 0.0061 | - |
| 0.1872 | 9550 | 0.0039 | - |
| 0.1882 | 9600 | 0.003 | - |
| 0.1892 | 9650 | 0.0021 | - |
| 0.1901 | 9700 | 0.0043 | - |
| 0.1911 | 9750 | 0.0136 | - |
| 0.1921 | 9800 | 0.0081 | - |
| 0.1931 | 9850 | 0.0139 | - |
| 0.1941 | 9900 | 0.017 | - |
| 0.1950 | 9950 | 0.0076 | - |
| 0.1960 | 10000 | 0.0053 | 0.3758 |
| 0.1970 | 10050 | 0.002 | - |
| 0.1980 | 10100 | 0.0052 | - |
| 0.1990 | 10150 | 0.0017 | - |
| 0.1999 | 10200 | 0.0006 | - |
| 0.2009 | 10250 | 0.0007 | - |
| 0.2019 | 10300 | 0.0002 | - |
| 0.2029 | 10350 | 0.0004 | - |
| 0.2039 | 10400 | 0.0009 | - |
| 0.2048 | 10450 | 0.0013 | - |
| 0.2058 | 10500 | 0.0017 | - |
| 0.2068 | 10550 | 0.0008 | - |
| 0.2078 | 10600 | 0.0007 | - |
| 0.2088 | 10650 | 0.0017 | - |
| 0.2097 | 10700 | 0.0016 | - |
| 0.2107 | 10750 | 0.0038 | - |
| 0.2117 | 10800 | 0.0109 | - |
| 0.2127 | 10850 | 0.0037 | - |
| 0.2137 | 10900 | 0.0027 | - |
| 0.2146 | 10950 | 0.0028 | - |
| 0.2156 | 11000 | 0.001 | - |
| 0.2166 | 11050 | 0.0013 | - |
| 0.2176 | 11100 | 0.0012 | - |
| 0.2186 | 11150 | 0.0017 | - |
| 0.2195 | 11200 | 0.0026 | - |
| 0.2205 | 11250 | 0.007 | - |
| 0.2215 | 11300 | 0.0096 | - |
| 0.2225 | 11350 | 0.0052 | - |
| 0.2235 | 11400 | 0.003 | - |
| 0.2244 | 11450 | 0.0028 | - |
| 0.2254 | 11500 | 0.0064 | - |
| 0.2264 | 11550 | 0.0035 | - |
| 0.2274 | 11600 | 0.0076 | - |
| 0.2284 | 11650 | 0.008 | - |
| 0.2293 | 11700 | 0.0062 | - |
| 0.2303 | 11750 | 0.0045 | - |
| 0.2313 | 11800 | 0.0022 | - |
| 0.2323 | 11850 | 0.0007 | - |
| 0.2333 | 11900 | 0.0011 | - |
| 0.2342 | 11950 | 0.0014 | - |
| 0.2352 | 12000 | 0.0007 | - |
| 0.2362 | 12050 | 0.0015 | - |
| 0.2372 | 12100 | 0.0007 | - |
| 0.2382 | 12150 | 0.0009 | - |
| 0.2392 | 12200 | 0.0074 | - |
| 0.2401 | 12250 | 0.0031 | - |
| 0.2411 | 12300 | 0.0015 | - |
| 0.2421 | 12350 | 0.0021 | - |
| 0.2431 | 12400 | 0.0014 | - |
| 0.2441 | 12450 | 0.0014 | - |
| 0.2450 | 12500 | 0.0034 | - |
| 0.2460 | 12550 | 0.0004 | - |
| 0.2470 | 12600 | 0.0004 | - |
| 0.2480 | 12650 | 0.0007 | - |
| 0.2490 | 12700 | 0.0012 | - |
| 0.2499 | 12750 | 0.0004 | - |
| 0.2509 | 12800 | 0.0008 | - |
| 0.2519 | 12850 | 0.0006 | - |
| 0.2529 | 12900 | 0.0007 | - |
| 0.2539 | 12950 | 0.0005 | - |
| 0.2548 | 13000 | 0.0002 | - |
| 0.2558 | 13050 | 0.0008 | - |
| 0.2568 | 13100 | 0.0009 | - |
| 0.2578 | 13150 | 0.0012 | - |
| 0.2588 | 13200 | 0.0009 | - |
| 0.2597 | 13250 | 0.0013 | - |
| 0.2607 | 13300 | 0.0006 | - |
| 0.2617 | 13350 | 0.0013 | - |
| 0.2627 | 13400 | 0.0007 | - |
| 0.2637 | 13450 | 0.0028 | - |
| 0.2646 | 13500 | 0.0013 | - |
| 0.2656 | 13550 | 0.0 | - |
| 0.2666 | 13600 | 0.0007 | - |
| 0.2676 | 13650 | 0.0012 | - |
| 0.2686 | 13700 | 0.0035 | - |
| 0.2695 | 13750 | 0.01 | - |
| 0.2705 | 13800 | 0.0217 | - |
| 0.2715 | 13850 | 0.0141 | - |
| 0.2725 | 13900 | 0.0132 | - |
| 0.2735 | 13950 | 0.0111 | - |
| 0.2744 | 14000 | 0.013 | - |
| 0.2754 | 14050 | 0.0092 | - |
| 0.2764 | 14100 | 0.0025 | - |
| 0.2774 | 14150 | 0.0035 | - |
| 0.2784 | 14200 | 0.0051 | - |
| 0.2793 | 14250 | 0.0102 | - |
| 0.2803 | 14300 | 0.0093 | - |
| 0.2813 | 14350 | 0.0052 | - |
| 0.2823 | 14400 | 0.004 | - |
| 0.2833 | 14450 | 0.0057 | - |
| 0.2842 | 14500 | 0.0033 | - |
| 0.2852 | 14550 | 0.0065 | - |
| 0.2862 | 14600 | 0.0038 | - |
| 0.2872 | 14650 | 0.0037 | - |
| 0.2882 | 14700 | 0.0071 | - |
| 0.2891 | 14750 | 0.0079 | - |
| 0.2901 | 14800 | 0.0073 | - |
| 0.2911 | 14850 | 0.0066 | - |
| 0.2921 | 14900 | 0.014 | - |
| 0.2931 | 14950 | 0.0081 | - |
| 0.2940 | 15000 | 0.0032 | 0.3803 |
| 0.2950 | 15050 | 0.005 | - |
| 0.2960 | 15100 | 0.0062 | - |
| 0.2970 | 15150 | 0.013 | - |
| 0.2980 | 15200 | 0.0027 | - |
| 0.2989 | 15250 | 0.005 | - |
| 0.2999 | 15300 | 0.0068 | - |
| 0.3009 | 15350 | 0.0041 | - |
| 0.3019 | 15400 | 0.0042 | - |
| 0.3029 | 15450 | 0.0028 | - |
| 0.3038 | 15500 | 0.0089 | - |
| 0.3048 | 15550 | 0.0072 | - |
| 0.3058 | 15600 | 0.0031 | - |
| 0.3068 | 15650 | 0.0061 | - |
| 0.3078 | 15700 | 0.0086 | - |
| 0.3087 | 15750 | 0.0051 | - |
| 0.3097 | 15800 | 0.0081 | - |
| 0.3107 | 15850 | 0.0078 | - |
| 0.3117 | 15900 | 0.0032 | - |
| 0.3127 | 15950 | 0.0012 | - |
| 0.3136 | 16000 | 0.0019 | - |
| 0.3146 | 16050 | 0.0013 | - |
| 0.3156 | 16100 | 0.0027 | - |
| 0.3166 | 16150 | 0.0017 | - |
| 0.3176 | 16200 | 0.0013 | - |
| 0.3185 | 16250 | 0.0025 | - |
| 0.3195 | 16300 | 0.0026 | - |
| 0.3205 | 16350 | 0.0021 | - |
| 0.3215 | 16400 | 0.0007 | - |
| 0.3225 | 16450 | 0.0019 | - |
| 0.3234 | 16500 | 0.0 | - |
| 0.3244 | 16550 | 0.0005 | - |
| 0.3254 | 16600 | 0.0019 | - |
| 0.3264 | 16650 | 0.0017 | - |
| 0.3274 | 16700 | 0.0019 | - |
| 0.3283 | 16750 | 0.0025 | - |
| 0.3293 | 16800 | 0.0037 | - |
| 0.3303 | 16850 | 0.0032 | - |
| 0.3313 | 16900 | 0.0029 | - |
| 0.3323 | 16950 | 0.001 | - |
| 0.3332 | 17000 | 0.0042 | - |
| 0.3342 | 17050 | 0.0013 | - |
| 0.3352 | 17100 | 0.0025 | - |
| 0.3362 | 17150 | 0.0006 | - |
| 0.3372 | 17200 | 0.0 | - |
| 0.3381 | 17250 | 0.0006 | - |
| 0.3391 | 17300 | 0.0 | - |
| 0.3401 | 17350 | 0.0 | - |
| 0.3411 | 17400 | 0.0 | - |
| 0.3421 | 17450 | 0.0 | - |
| 0.3430 | 17500 | 0.0006 | - |
| 0.3440 | 17550 | 0.0 | - |
| 0.3450 | 17600 | 0.0001 | - |
| 0.3460 | 17650 | 0.0026 | - |
| 0.3470 | 17700 | 0.0013 | - |
| 0.3479 | 17750 | 0.0053 | - |
| 0.3489 | 17800 | 0.005 | - |
| 0.3499 | 17850 | 0.0032 | - |
| 0.3509 | 17900 | 0.0051 | - |
| 0.3519 | 17950 | 0.002 | - |
| 0.3528 | 18000 | 0.0025 | - |
| 0.3538 | 18050 | 0.0006 | - |
| 0.3548 | 18100 | 0.0004 | - |
| 0.3558 | 18150 | 0.0027 | - |
| 0.3568 | 18200 | 0.0013 | - |
| 0.3577 | 18250 | 0.0013 | - |
| 0.3587 | 18300 | 0.0007 | - |
| 0.3597 | 18350 | 0.0015 | - |
| 0.3607 | 18400 | 0.0006 | - |
| 0.3617 | 18450 | 0.0018 | - |
| 0.3626 | 18500 | 0.0021 | - |
| 0.3636 | 18550 | 0.0034 | - |
| 0.3646 | 18600 | 0.0037 | - |
| 0.3656 | 18650 | 0.005 | - |
| 0.3666 | 18700 | 0.0027 | - |
| 0.3675 | 18750 | 0.0024 | - |
| 0.3685 | 18800 | 0.0 | - |
| 0.3695 | 18850 | 0.0 | - |
| 0.3705 | 18900 | 0.0006 | - |
| 0.3715 | 18950 | 0.0008 | - |
| 0.3724 | 19000 | 0.005 | - |
| 0.3734 | 19050 | 0.003 | - |
| 0.3744 | 19100 | 0.0011 | - |
| 0.3754 | 19150 | 0.0006 | - |
| 0.3764 | 19200 | 0.0 | - |
| 0.3773 | 19250 | 0.0 | - |
| 0.3783 | 19300 | 0.0001 | - |
| 0.3793 | 19350 | 0.003 | - |
| 0.3803 | 19400 | 0.0 | - |
| 0.3813 | 19450 | 0.0 | - |
| 0.3822 | 19500 | 0.0017 | - |
| 0.3832 | 19550 | 0.001 | - |
| 0.3842 | 19600 | 0.0017 | - |
| 0.3852 | 19650 | 0.0006 | - |
| 0.3862 | 19700 | 0.0 | - |
| 0.3871 | 19750 | 0.0 | - |
| 0.3881 | 19800 | 0.0022 | - |
| 0.3891 | 19850 | 0.0 | - |
| 0.3901 | 19900 | 0.0 | - |
| 0.3911 | 19950 | 0.0 | - |
| 0.3920 | 20000 | 0.0 | 0.3965 |
| 0.3930 | 20050 | 0.0 | - |
| 0.3940 | 20100 | 0.0005 | - |
| 0.3950 | 20150 | 0.0009 | - |
| 0.3960 | 20200 | 0.0 | - |
| 0.3969 | 20250 | 0.0 | - |
| 0.3979 | 20300 | 0.0016 | - |
| 0.3989 | 20350 | 0.0053 | - |
| 0.3999 | 20400 | 0.0 | - |
| 0.4009 | 20450 | 0.0017 | - |
| 0.4019 | 20500 | 0.001 | - |
| 0.4028 | 20550 | 0.0004 | - |
| 0.4038 | 20600 | 0.0006 | - |
| 0.4048 | 20650 | 0.0006 | - |
| 0.4058 | 20700 | 0.0006 | - |
| 0.4068 | 20750 | 0.0012 | - |
| 0.4077 | 20800 | 0.002 | - |
| 0.4087 | 20850 | 0.0006 | - |
| 0.4097 | 20900 | 0.0016 | - |
| 0.4107 | 20950 | 0.0013 | - |
| 0.4117 | 21000 | 0.0029 | - |
| 0.4126 | 21050 | 0.0011 | - |
| 0.4136 | 21100 | 0.0 | - |
| 0.4146 | 21150 | 0.0 | - |
| 0.4156 | 21200 | 0.0 | - |
| 0.4166 | 21250 | 0.0006 | - |
| 0.4175 | 21300 | 0.0013 | - |
| 0.4185 | 21350 | 0.0013 | - |
| 0.4195 | 21400 | 0.0066 | - |
| 0.4205 | 21450 | 0.0001 | - |
| 0.4215 | 21500 | 0.0001 | - |
| 0.4224 | 21550 | 0.0 | - |
| 0.4234 | 21600 | 0.0018 | - |
| 0.4244 | 21650 | 0.0056 | - |
| 0.4254 | 21700 | 0.0025 | - |
| 0.4264 | 21750 | 0.0028 | - |
| 0.4273 | 21800 | 0.0013 | - |
| 0.4283 | 21850 | 0.0025 | - |
| 0.4293 | 21900 | 0.0024 | - |
| 0.4303 | 21950 | 0.0006 | - |
| 0.4313 | 22000 | 0.0006 | - |
| 0.4322 | 22050 | 0.0 | - |
| 0.4332 | 22100 | 0.0 | - |
| 0.4342 | 22150 | 0.0 | - |
| 0.4352 | 22200 | 0.0 | - |
| 0.4362 | 22250 | 0.0 | - |
| 0.4371 | 22300 | 0.0 | - |
| 0.4381 | 22350 | 0.0 | - |
| 0.4391 | 22400 | 0.0 | - |
| 0.4401 | 22450 | 0.0 | - |
| 0.4411 | 22500 | 0.0 | - |
| 0.4420 | 22550 | 0.0 | - |
| 0.4430 | 22600 | 0.0 | - |
| 0.4440 | 22650 | 0.0 | - |
| 0.4450 | 22700 | 0.0 | - |
| 0.4460 | 22750 | 0.0 | - |
| 0.4469 | 22800 | 0.0 | - |
| 0.4479 | 22850 | 0.0 | - |
| 0.4489 | 22900 | 0.0 | - |
| 0.4499 | 22950 | 0.0 | - |
| 0.4509 | 23000 | 0.0 | - |
| 0.4518 | 23050 | 0.0 | - |
| 0.4528 | 23100 | 0.0 | - |
| 0.4538 | 23150 | 0.0 | - |
| 0.4548 | 23200 | 0.0 | - |
| 0.4558 | 23250 | 0.0 | - |
| 0.4567 | 23300 | 0.0 | - |
| 0.4577 | 23350 | 0.0 | - |
| 0.4587 | 23400 | 0.0 | - |
| 0.4597 | 23450 | 0.0 | - |
| 0.4607 | 23500 | 0.0 | - |
| 0.4616 | 23550 | 0.0 | - |
| 0.4626 | 23600 | 0.0 | - |
| 0.4636 | 23650 | 0.0 | - |
| 0.4646 | 23700 | 0.0 | - |
| 0.4656 | 23750 | 0.0 | - |
| 0.4665 | 23800 | 0.0 | - |
| 0.4675 | 23850 | 0.0 | - |
| 0.4685 | 23900 | 0.0 | - |
| 0.4695 | 23950 | 0.0 | - |
| 0.4705 | 24000 | 0.0 | - |
| 0.4714 | 24050 | 0.0 | - |
| 0.4724 | 24100 | 0.0 | - |
| 0.4734 | 24150 | 0.0 | - |
| 0.4744 | 24200 | 0.0 | - |
| 0.4754 | 24250 | 0.0006 | - |
| 0.4763 | 24300 | 0.0029 | - |
| 0.4773 | 24350 | 0.0072 | - |
| 0.4783 | 24400 | 0.0012 | - |
| 0.4793 | 24450 | 0.0029 | - |
| 0.4803 | 24500 | 0.0039 | - |
| 0.4812 | 24550 | 0.0013 | - |
| 0.4822 | 24600 | 0.0006 | - |
| 0.4832 | 24650 | 0.0025 | - |
| 0.4842 | 24700 | 0.0 | - |
| 0.4852 | 24750 | 0.0006 | - |
| 0.4861 | 24800 | 0.0019 | - |
| 0.4871 | 24850 | 0.0011 | - |
| 0.4881 | 24900 | 0.0025 | - |
| 0.4891 | 24950 | 0.0019 | - |
| 0.4901 | 25000 | 0.0006 | 0.4125 |
| 0.4910 | 25050 | 0.0006 | - |
| 0.4920 | 25100 | 0.0006 | - |
| 0.4930 | 25150 | 0.003 | - |
| 0.4940 | 25200 | 0.0031 | - |
| 0.4950 | 25250 | 0.0018 | - |
| 0.4959 | 25300 | 0.0024 | - |
| 0.4969 | 25350 | 0.0045 | - |
| 0.4979 | 25400 | 0.0034 | - |
| 0.4989 | 25450 | 0.0025 | - |
| 0.4999 | 25500 | 0.0019 | - |
| 0.5008 | 25550 | 0.0019 | - |
| 0.5018 | 25600 | 0.0007 | - |
| 0.5028 | 25650 | 0.0 | - |
| 0.5038 | 25700 | 0.0019 | - |
| 0.5048 | 25750 | 0.0006 | - |
| 0.5057 | 25800 | 0.0019 | - |
| 0.5067 | 25850 | 0.0006 | - |
| 0.5077 | 25900 | 0.0016 | - |
| 0.5087 | 25950 | 0.0006 | - |
| 0.5097 | 26000 | 0.0029 | - |
| 0.5106 | 26050 | 0.0012 | - |
| 0.5116 | 26100 | 0.0013 | - |
| 0.5126 | 26150 | 0.0016 | - |
| 0.5136 | 26200 | 0.0021 | - |
| 0.5146 | 26250 | 0.0006 | - |
| 0.5155 | 26300 | 0.0013 | - |
| 0.5165 | 26350 | 0.003 | - |
| 0.5175 | 26400 | 0.0007 | - |
| 0.5185 | 26450 | 0.0025 | - |
| 0.5195 | 26500 | 0.0 | - |
| 0.5204 | 26550 | 0.0012 | - |
| 0.5214 | 26600 | 0.0 | - |
| 0.5224 | 26650 | 0.0016 | - |
| 0.5234 | 26700 | 0.0006 | - |
| 0.5244 | 26750 | 0.0001 | - |
| 0.5253 | 26800 | 0.0 | - |
| 0.5263 | 26850 | 0.0 | - |
| 0.5273 | 26900 | 0.0 | - |
| 0.5283 | 26950 | 0.0 | - |
| 0.5293 | 27000 | 0.0 | - |
| 0.5302 | 27050 | 0.0 | - |
| 0.5312 | 27100 | 0.0 | - |
| 0.5322 | 27150 | 0.0 | - |
| 0.5332 | 27200 | 0.0 | - |
| 0.5342 | 27250 | 0.0 | - |
| 0.5351 | 27300 | 0.0 | - |
| 0.5361 | 27350 | 0.0 | - |
| 0.5371 | 27400 | 0.0 | - |
| 0.5381 | 27450 | 0.0 | - |
| 0.5391 | 27500 | 0.0 | - |
| 0.5400 | 27550 | 0.0 | - |
| 0.5410 | 27600 | 0.0 | - |
| 0.5420 | 27650 | 0.0 | - |
| 0.5430 | 27700 | 0.0 | - |
| 0.5440 | 27750 | 0.0 | - |
| 0.5449 | 27800 | 0.0 | - |
| 0.5459 | 27850 | 0.0 | - |
| 0.5469 | 27900 | 0.0 | - |
| 0.5479 | 27950 | 0.0 | - |
| 0.5489 | 28000 | 0.0 | - |
| 0.5498 | 28050 | 0.0 | - |
| 0.5508 | 28100 | 0.0017 | - |
| 0.5518 | 28150 | 0.0 | - |
| 0.5528 | 28200 | 0.0018 | - |
| 0.5538 | 28250 | 0.0042 | - |
| 0.5547 | 28300 | 0.0007 | - |
| 0.5557 | 28350 | 0.0 | - |
| 0.5567 | 28400 | 0.0006 | - |
| 0.5577 | 28450 | 0.0006 | - |
| 0.5587 | 28500 | 0.0006 | - |
| 0.5597 | 28550 | 0.0 | - |
| 0.5606 | 28600 | 0.0 | - |
| 0.5616 | 28650 | 0.0012 | - |
| 0.5626 | 28700 | 0.0 | - |
| 0.5636 | 28750 | 0.0 | - |
| 0.5646 | 28800 | 0.0 | - |
| 0.5655 | 28850 | 0.0 | - |
| 0.5665 | 28900 | 0.0017 | - |
| 0.5675 | 28950 | 0.0006 | - |
| 0.5685 | 29000 | 0.0 | - |
| 0.5695 | 29050 | 0.0 | - |
| 0.5704 | 29100 | 0.0 | - |
| 0.5714 | 29150 | 0.0 | - |
| 0.5724 | 29200 | 0.0 | - |
| 0.5734 | 29250 | 0.0 | - |
| 0.5744 | 29300 | 0.0 | - |
| 0.5753 | 29350 | 0.0 | - |
| 0.5763 | 29400 | 0.0 | - |
| 0.5773 | 29450 | 0.0 | - |
| 0.5783 | 29500 | 0.0 | - |
| 0.5793 | 29550 | 0.0 | - |
| 0.5802 | 29600 | 0.0 | - |
| 0.5812 | 29650 | 0.0 | - |
| 0.5822 | 29700 | 0.0 | - |
| 0.5832 | 29750 | 0.0 | - |
| 0.5842 | 29800 | 0.0 | - |
| 0.5851 | 29850 | 0.0 | - |
| 0.5861 | 29900 | 0.0 | - |
| 0.5871 | 29950 | 0.0 | - |
| 0.5881 | 30000 | 0.0 | 0.3633 |
| 0.5891 | 30050 | 0.0 | - |
| 0.5900 | 30100 | 0.0 | - |
| 0.5910 | 30150 | 0.0 | - |
| 0.5920 | 30200 | 0.0 | - |
| 0.5930 | 30250 | 0.0 | - |
| 0.5940 | 30300 | 0.0 | - |
| 0.5949 | 30350 | 0.0 | - |
| 0.5959 | 30400 | 0.0 | - |
| 0.5969 | 30450 | 0.0 | - |
| 0.5979 | 30500 | 0.0 | - |
| 0.5989 | 30550 | 0.0 | - |
| 0.5998 | 30600 | 0.0 | - |
| 0.6008 | 30650 | 0.0 | - |
| 0.6018 | 30700 | 0.0 | - |
| 0.6028 | 30750 | 0.0 | - |
| 0.6038 | 30800 | 0.0 | - |
| 0.6047 | 30850 | 0.0 | - |
| 0.6057 | 30900 | 0.0 | - |
| 0.6067 | 30950 | 0.0 | - |
| 0.6077 | 31000 | 0.0 | - |
| 0.6087 | 31050 | 0.0 | - |
| 0.6096 | 31100 | 0.0 | - |
| 0.6106 | 31150 | 0.0 | - |
| 0.6116 | 31200 | 0.0 | - |
| 0.6126 | 31250 | 0.0 | - |
| 0.6136 | 31300 | 0.0 | - |
| 0.6145 | 31350 | 0.0 | - |
| 0.6155 | 31400 | 0.0 | - |
| 0.6165 | 31450 | 0.0 | - |
| 0.6175 | 31500 | 0.0 | - |
| 0.6185 | 31550 | 0.0 | - |
| 0.6194 | 31600 | 0.0 | - |
| 0.6204 | 31650 | 0.0 | - |
| 0.6214 | 31700 | 0.0 | - |
| 0.6224 | 31750 | 0.0 | - |
| 0.6234 | 31800 | 0.0 | - |
| 0.6243 | 31850 | 0.0 | - |
| 0.6253 | 31900 | 0.0 | - |
| 0.6263 | 31950 | 0.0 | - |
| 0.6273 | 32000 | 0.0 | - |
| 0.6283 | 32050 | 0.0 | - |
| 0.6292 | 32100 | 0.0 | - |
| 0.6302 | 32150 | 0.0 | - |
| 0.6312 | 32200 | 0.0 | - |
| 0.6322 | 32250 | 0.0 | - |
| 0.6332 | 32300 | 0.0 | - |
| 0.6341 | 32350 | 0.0 | - |
| 0.6351 | 32400 | 0.0 | - |
| 0.6361 | 32450 | 0.0 | - |
| 0.6371 | 32500 | 0.0 | - |
| 0.6381 | 32550 | 0.0 | - |
| 0.6390 | 32600 | 0.0 | - |
| 0.6400 | 32650 | 0.0 | - |
| 0.6410 | 32700 | 0.0 | - |
| 0.6420 | 32750 | 0.0 | - |
| 0.6430 | 32800 | 0.0 | - |
| 0.6439 | 32850 | 0.0 | - |
| 0.6449 | 32900 | 0.0 | - |
| 0.6459 | 32950 | 0.0 | - |
| 0.6469 | 33000 | 0.0 | - |
| 0.6479 | 33050 | 0.0 | - |
| 0.6488 | 33100 | 0.0 | - |
| 0.6498 | 33150 | 0.0 | - |
| 0.6508 | 33200 | 0.0 | - |
| 0.6518 | 33250 | 0.0 | - |
| 0.6528 | 33300 | 0.0 | - |
| 0.6537 | 33350 | 0.0 | - |
| 0.6547 | 33400 | 0.0 | - |
| 0.6557 | 33450 | 0.0 | - |
| 0.6567 | 33500 | 0.0 | - |
| 0.6577 | 33550 | 0.0 | - |
| 0.6586 | 33600 | 0.0 | - |
| 0.6596 | 33650 | 0.0 | - |
| 0.6606 | 33700 | 0.0031 | - |
| 0.6616 | 33750 | 0.0045 | - |
| 0.6626 | 33800 | 0.0026 | - |
| 0.6635 | 33850 | 0.0013 | - |
| 0.6645 | 33900 | 0.0008 | - |
| 0.6655 | 33950 | 0.0006 | - |
| 0.6665 | 34000 | 0.0007 | - |
| 0.6675 | 34050 | 0.0009 | - |
| 0.6684 | 34100 | 0.0 | - |
| 0.6694 | 34150 | 0.0 | - |
| 0.6704 | 34200 | 0.0 | - |
| 0.6714 | 34250 | 0.0 | - |
| 0.6724 | 34300 | 0.0 | - |
| 0.6733 | 34350 | 0.0009 | - |
| 0.6743 | 34400 | 0.0 | - |
| 0.6753 | 34450 | 0.0005 | - |
| 0.6763 | 34500 | 0.0019 | - |
| 0.6773 | 34550 | 0.0055 | - |
| 0.6782 | 34600 | 0.0019 | - |
| 0.6792 | 34650 | 0.0019 | - |
| 0.6802 | 34700 | 0.0038 | - |
| 0.6812 | 34750 | 0.0006 | - |
| 0.6822 | 34800 | 0.0013 | - |
| 0.6831 | 34850 | 0.0006 | - |
| 0.6841 | 34900 | 0.0025 | - |
| 0.6851 | 34950 | 0.0019 | - |
| 0.6861 | 35000 | 0.0 | 0.3883 |
| 0.6871 | 35050 | 0.0013 | - |
| 0.6880 | 35100 | 0.0021 | - |
| 0.6890 | 35150 | 0.0019 | - |
| 0.6900 | 35200 | 0.0025 | - |
| 0.6910 | 35250 | 0.0 | - |
| 0.6920 | 35300 | 0.0 | - |
| 0.6929 | 35350 | 0.0019 | - |
| 0.6939 | 35400 | 0.0031 | - |
| 0.6949 | 35450 | 0.0006 | - |
| 0.6959 | 35500 | 0.0019 | - |
| 0.6969 | 35550 | 0.0 | - |
| 0.6978 | 35600 | 0.0019 | - |
| 0.6988 | 35650 | 0.0006 | - |
| 0.6998 | 35700 | 0.0013 | - |
| 0.7008 | 35750 | 0.0006 | - |
| 0.7018 | 35800 | 0.0 | - |
| 0.7027 | 35850 | 0.0 | - |
| 0.7037 | 35900 | 0.0 | - |
| 0.7047 | 35950 | 0.0 | - |
| 0.7057 | 36000 | 0.0 | - |
| 0.7067 | 36050 | 0.0 | - |
| 0.7076 | 36100 | 0.0 | - |
| 0.7086 | 36150 | 0.0 | - |
| 0.7096 | 36200 | 0.0 | - |
| 0.7106 | 36250 | 0.0 | - |
| 0.7116 | 36300 | 0.0 | - |
| 0.7125 | 36350 | 0.0 | - |
| 0.7135 | 36400 | 0.0 | - |
| 0.7145 | 36450 | 0.0 | - |
| 0.7155 | 36500 | 0.0 | - |
| 0.7165 | 36550 | 0.0 | - |
| 0.7175 | 36600 | 0.0 | - |
| 0.7184 | 36650 | 0.0 | - |
| 0.7194 | 36700 | 0.0 | - |
| 0.7204 | 36750 | 0.0 | - |
| 0.7214 | 36800 | 0.0 | - |
| 0.7224 | 36850 | 0.0 | - |
| 0.7233 | 36900 | 0.0 | - |
| 0.7243 | 36950 | 0.0 | - |
| 0.7253 | 37000 | 0.0 | - |
| 0.7263 | 37050 | 0.0 | - |
| 0.7273 | 37100 | 0.0 | - |
| 0.7282 | 37150 | 0.0 | - |
| 0.7292 | 37200 | 0.0 | - |
| 0.7302 | 37250 | 0.0 | - |
| 0.7312 | 37300 | 0.0 | - |
| 0.7322 | 37350 | 0.0 | - |
| 0.7331 | 37400 | 0.0 | - |
| 0.7341 | 37450 | 0.0 | - |
| 0.7351 | 37500 | 0.0 | - |
| 0.7361 | 37550 | 0.0 | - |
| 0.7371 | 37600 | 0.0 | - |
| 0.7380 | 37650 | 0.0 | - |
| 0.7390 | 37700 | 0.0 | - |
| 0.7400 | 37750 | 0.0 | - |
| 0.7410 | 37800 | 0.0 | - |
| 0.7420 | 37850 | 0.0 | - |
| 0.7429 | 37900 | 0.0 | - |
| 0.7439 | 37950 | 0.0 | - |
| 0.7449 | 38000 | 0.0 | - |
| 0.7459 | 38050 | 0.0 | - |
| 0.7469 | 38100 | 0.0 | - |
| 0.7478 | 38150 | 0.0 | - |
| 0.7488 | 38200 | 0.0 | - |
| 0.7498 | 38250 | 0.0 | - |
| 0.7508 | 38300 | 0.0012 | - |
| 0.7518 | 38350 | 0.0012 | - |
| 0.7527 | 38400 | 0.002 | - |
| 0.7537 | 38450 | 0.0001 | - |
| 0.7547 | 38500 | 0.0003 | - |
| 0.7557 | 38550 | 0.0002 | - |
| 0.7567 | 38600 | 0.0 | - |
| 0.7576 | 38650 | 0.0 | - |
| 0.7586 | 38700 | 0.0 | - |
| 0.7596 | 38750 | 0.0 | - |
| 0.7606 | 38800 | 0.0 | - |
| 0.7616 | 38850 | 0.0 | - |
| 0.7625 | 38900 | 0.0006 | - |
| 0.7635 | 38950 | 0.0002 | - |
| 0.7645 | 39000 | 0.0006 | - |
| 0.7655 | 39050 | 0.0 | - |
| 0.7665 | 39100 | 0.0 | - |
| 0.7674 | 39150 | 0.0 | - |
| 0.7684 | 39200 | 0.0 | - |
| 0.7694 | 39250 | 0.0 | - |
| 0.7704 | 39300 | 0.0 | - |
| 0.7714 | 39350 | 0.0 | - |
| 0.7723 | 39400 | 0.003 | - |
| 0.7733 | 39450 | 0.0001 | - |
| 0.7743 | 39500 | 0.0006 | - |
| 0.7753 | 39550 | 0.0 | - |
| 0.7763 | 39600 | 0.0 | - |
| 0.7772 | 39650 | 0.0 | - |
| 0.7782 | 39700 | 0.0 | - |
| 0.7792 | 39750 | 0.0 | - |
| 0.7802 | 39800 | 0.0 | - |
| 0.7812 | 39850 | 0.0 | - |
| 0.7821 | 39900 | 0.0 | - |
| 0.7831 | 39950 | 0.0006 | - |
| 0.7841 | 40000 | 0.0007 | 0.4086 |
| 0.7851 | 40050 | 0.0006 | - |
| 0.7861 | 40100 | 0.0 | - |
| 0.7870 | 40150 | 0.0 | - |
| 0.7880 | 40200 | 0.0 | - |
| 0.7890 | 40250 | 0.0006 | - |
| 0.7900 | 40300 | 0.0006 | - |
| 0.7910 | 40350 | 0.0 | - |
| 0.7919 | 40400 | 0.0 | - |
| 0.7929 | 40450 | 0.0 | - |
| 0.7939 | 40500 | 0.0 | - |
| 0.7949 | 40550 | 0.0 | - |
| 0.7959 | 40600 | 0.0 | - |
| 0.7968 | 40650 | 0.0 | - |
| 0.7978 | 40700 | 0.0 | - |
| 0.7988 | 40750 | 0.0 | - |
| 0.7998 | 40800 | 0.0 | - |
| 0.8008 | 40850 | 0.0 | - |
| 0.8017 | 40900 | 0.0 | - |
| 0.8027 | 40950 | 0.0 | - |
| 0.8037 | 41000 | 0.0 | - |
| 0.8047 | 41050 | 0.0 | - |
| 0.8057 | 41100 | 0.0 | - |
| 0.8066 | 41150 | 0.0 | - |
| 0.8076 | 41200 | 0.0 | - |
| 0.8086 | 41250 | 0.0 | - |
| 0.8096 | 41300 | 0.0001 | - |
| 0.8106 | 41350 | 0.0007 | - |
| 0.8115 | 41400 | 0.0 | - |
| 0.8125 | 41450 | 0.0 | - |
| 0.8135 | 41500 | 0.0 | - |
| 0.8145 | 41550 | 0.0 | - |
| 0.8155 | 41600 | 0.0 | - |
| 0.8164 | 41650 | 0.0 | - |
| 0.8174 | 41700 | 0.0 | - |
| 0.8184 | 41750 | 0.0 | - |
| 0.8194 | 41800 | 0.0 | - |
| 0.8204 | 41850 | 0.0 | - |
| 0.8213 | 41900 | 0.0 | - |
| 0.8223 | 41950 | 0.0 | - |
| 0.8233 | 42000 | 0.0 | - |
| 0.8243 | 42050 | 0.0 | - |
| 0.8253 | 42100 | 0.0 | - |
| 0.8262 | 42150 | 0.0 | - |
| 0.8272 | 42200 | 0.0 | - |
| 0.8282 | 42250 | 0.0 | - |
| 0.8292 | 42300 | 0.0 | - |
| 0.8302 | 42350 | 0.0 | - |
| 0.8311 | 42400 | 0.0 | - |
| 0.8321 | 42450 | 0.0 | - |
| 0.8331 | 42500 | 0.0 | - |
| 0.8341 | 42550 | 0.0 | - |
| 0.8351 | 42600 | 0.0 | - |
| 0.8360 | 42650 | 0.0 | - |
| 0.8370 | 42700 | 0.0 | - |
| 0.8380 | 42750 | 0.0 | - |
| 0.8390 | 42800 | 0.0 | - |
| 0.8400 | 42850 | 0.0 | - |
| 0.8409 | 42900 | 0.0 | - |
| 0.8419 | 42950 | 0.0 | - |
| 0.8429 | 43000 | 0.0 | - |
| 0.8439 | 43050 | 0.0 | - |
| 0.8449 | 43100 | 0.0 | - |
| 0.8458 | 43150 | 0.0 | - |
| 0.8468 | 43200 | 0.0 | - |
| 0.8478 | 43250 | 0.0 | - |
| 0.8488 | 43300 | 0.0 | - |
| 0.8498 | 43350 | 0.0 | - |
| 0.8507 | 43400 | 0.0 | - |
| 0.8517 | 43450 | 0.0 | - |
| 0.8527 | 43500 | 0.0 | - |
| 0.8537 | 43550 | 0.0 | - |
| 0.8547 | 43600 | 0.0 | - |
| 0.8556 | 43650 | 0.0 | - |
| 0.8566 | 43700 | 0.0 | - |
| 0.8576 | 43750 | 0.0 | - |
| 0.8586 | 43800 | 0.0 | - |
| 0.8596 | 43850 | 0.0 | - |
| 0.8605 | 43900 | 0.0 | - |
| 0.8615 | 43950 | 0.0 | - |
| 0.8625 | 44000 | 0.0 | - |
| 0.8635 | 44050 | 0.0 | - |
| 0.8645 | 44100 | 0.0 | - |
| 0.8654 | 44150 | 0.0 | - |
| 0.8664 | 44200 | 0.0 | - |
| 0.8674 | 44250 | 0.0 | - |
| 0.8684 | 44300 | 0.0 | - |
| 0.8694 | 44350 | 0.0 | - |
| 0.8703 | 44400 | 0.0 | - |
| 0.8713 | 44450 | 0.0 | - |
| 0.8723 | 44500 | 0.0 | - |
| 0.8733 | 44550 | 0.0 | - |
| 0.8743 | 44600 | 0.0 | - |
| 0.8752 | 44650 | 0.0 | - |
| 0.8762 | 44700 | 0.0 | - |
| 0.8772 | 44750 | 0.0 | - |
| 0.8782 | 44800 | 0.0 | - |
| 0.8792 | 44850 | 0.0 | - |
| 0.8802 | 44900 | 0.0 | - |
| 0.8811 | 44950 | 0.0 | - |
| 0.8821 | 45000 | 0.0 | 0.4173 |
| 0.8831 | 45050 | 0.0 | - |
| 0.8841 | 45100 | 0.0 | - |
| 0.8851 | 45150 | 0.0 | - |
| 0.8860 | 45200 | 0.0 | - |
| 0.8870 | 45250 | 0.0 | - |
| 0.8880 | 45300 | 0.0 | - |
| 0.8890 | 45350 | 0.0 | - |
| 0.8900 | 45400 | 0.0 | - |
| 0.8909 | 45450 | 0.0 | - |
| 0.8919 | 45500 | 0.0 | - |
| 0.8929 | 45550 | 0.0 | - |
| 0.8939 | 45600 | 0.0 | - |
| 0.8949 | 45650 | 0.0 | - |
| 0.8958 | 45700 | 0.0 | - |
| 0.8968 | 45750 | 0.0 | - |
| 0.8978 | 45800 | 0.0 | - |
| 0.8988 | 45850 | 0.0 | - |
| 0.8998 | 45900 | 0.0 | - |
| 0.9007 | 45950 | 0.0 | - |
| 0.9017 | 46000 | 0.0 | - |
| 0.9027 | 46050 | 0.0 | - |
| 0.9037 | 46100 | 0.0 | - |
| 0.9047 | 46150 | 0.0 | - |
| 0.9056 | 46200 | 0.0 | - |
| 0.9066 | 46250 | 0.0 | - |
| 0.9076 | 46300 | 0.0 | - |
| 0.9086 | 46350 | 0.0 | - |
| 0.9096 | 46400 | 0.0 | - |
| 0.9105 | 46450 | 0.0 | - |
| 0.9115 | 46500 | 0.0 | - |
| 0.9125 | 46550 | 0.0 | - |
| 0.9135 | 46600 | 0.0 | - |
| 0.9145 | 46650 | 0.0 | - |
| 0.9154 | 46700 | 0.0 | - |
| 0.9164 | 46750 | 0.0 | - |
| 0.9174 | 46800 | 0.0 | - |
| 0.9184 | 46850 | 0.0 | - |
| 0.9194 | 46900 | 0.0 | - |
| 0.9203 | 46950 | 0.0 | - |
| 0.9213 | 47000 | 0.0 | - |
| 0.9223 | 47050 | 0.0 | - |
| 0.9233 | 47100 | 0.0 | - |
| 0.9243 | 47150 | 0.0 | - |
| 0.9252 | 47200 | 0.0 | - |
| 0.9262 | 47250 | 0.0 | - |
| 0.9272 | 47300 | 0.0 | - |
| 0.9282 | 47350 | 0.0 | - |
| 0.9292 | 47400 | 0.0 | - |
| 0.9301 | 47450 | 0.0 | - |
| 0.9311 | 47500 | 0.0 | - |
| 0.9321 | 47550 | 0.0 | - |
| 0.9331 | 47600 | 0.0 | - |
| 0.9341 | 47650 | 0.0 | - |
| 0.9350 | 47700 | 0.0 | - |
| 0.9360 | 47750 | 0.0 | - |
| 0.9370 | 47800 | 0.0 | - |
| 0.9380 | 47850 | 0.0 | - |
| 0.9390 | 47900 | 0.0 | - |
| 0.9399 | 47950 | 0.0 | - |
| 0.9409 | 48000 | 0.0 | - |
| 0.9419 | 48050 | 0.0 | - |
| 0.9429 | 48100 | 0.0 | - |
| 0.9439 | 48150 | 0.0 | - |
| 0.9448 | 48200 | 0.0 | - |
| 0.9458 | 48250 | 0.0 | - |
| 0.9468 | 48300 | 0.0 | - |
| 0.9478 | 48350 | 0.0 | - |
| 0.9488 | 48400 | 0.0 | - |
| 0.9497 | 48450 | 0.0 | - |
| 0.9507 | 48500 | 0.0 | - |
| 0.9517 | 48550 | 0.0 | - |
| 0.9527 | 48600 | 0.0 | - |
| 0.9537 | 48650 | 0.0 | - |
| 0.9546 | 48700 | 0.0 | - |
| 0.9556 | 48750 | 0.0 | - |
| 0.9566 | 48800 | 0.0 | - |
| 0.9576 | 48850 | 0.0 | - |
| 0.9586 | 48900 | 0.0 | - |
| 0.9595 | 48950 | 0.0 | - |
| 0.9605 | 49000 | 0.0 | - |
| 0.9615 | 49050 | 0.0 | - |
| 0.9625 | 49100 | 0.0 | - |
| 0.9635 | 49150 | 0.0 | - |
| 0.9644 | 49200 | 0.0 | - |
| 0.9654 | 49250 | 0.0 | - |
| 0.9664 | 49300 | 0.0 | - |
| 0.9674 | 49350 | 0.0 | - |
| 0.9684 | 49400 | 0.0 | - |
| 0.9693 | 49450 | 0.0 | - |
| 0.9703 | 49500 | 0.0 | - |
| 0.9713 | 49550 | 0.0 | - |
| 0.9723 | 49600 | 0.0 | - |
| 0.9733 | 49650 | 0.0 | - |
| 0.9742 | 49700 | 0.0 | - |
| 0.9752 | 49750 | 0.0 | - |
| 0.9762 | 49800 | 0.0 | - |
| 0.9772 | 49850 | 0.0 | - |
| 0.9782 | 49900 | 0.0 | - |
| 0.9791 | 49950 | 0.0 | - |
| 0.9801 | 50000 | 0.0 | 0.4123 |
| 0.9811 | 50050 | 0.0 | - |
| 0.9821 | 50100 | 0.0 | - |
| 0.9831 | 50150 | 0.0 | - |
| 0.9840 | 50200 | 0.0 | - |
| 0.9850 | 50250 | 0.0 | - |
| 0.9860 | 50300 | 0.0 | - |
| 0.9870 | 50350 | 0.0 | - |
| 0.9880 | 50400 | 0.0 | - |
| 0.9889 | 50450 | 0.0 | - |
| 0.9899 | 50500 | 0.0 | - |
| 0.9909 | 50550 | 0.0 | - |
| 0.9919 | 50600 | 0.0 | - |
| 0.9929 | 50650 | 0.0 | - |
| 0.9938 | 50700 | 0.0 | - |
| 0.9948 | 50750 | 0.0 | - |
| 0.9958 | 50800 | 0.0 | - |
| 0.9968 | 50850 | 0.0 | - |
| 0.9978 | 50900 | 0.0 | - |
| 0.9987 | 50950 | 0.0 | - |
| 0.9997 | 51000 | 0.0 | - |
Framework Versions
- Python: 3.10.12
- SetFit: 1.1.2
- Sentence Transformers: 4.0.2
- Transformers: 4.51.0
- PyTorch: 2.6.0+cu124
- Datasets: 3.5.0
- Tokenizers: 0.21.1
Citation
BibTeX
@article{https://doi.org/10.48550/arxiv.2209.11055,
doi = {10.48550/ARXIV.2209.11055},
url = {https://arxiv.org/abs/2209.11055},
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Efficient Few-Shot Learning Without Prompts},
publisher = {arXiv},
year = {2022},
copyright = {Creative Commons Attribution 4.0 International}
}