metadata
library_name: setfit
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
metrics:
- accuracy
widget:
- text: >-
physiological metabolisms of seaweeds usually suffered climate changes in
the field. gracilariopsis lemaneiformis and ulva lactuca, collected from
nan ao island, shantou, china, were cultured under ambient and elevated
co2 supply , with low and high temperatures for weeks, aiming to compare
the difference of the main physiological metabolism between two seaweed
species in response to the elevated co2 and high temperature. at 15 , the
ph reduction in the culture medium caused by elevated co2 was larger in .
lemaneiformis than in . lactuca. at 25 , elevated co2 significantly
increased photosynthetic rates and maintained constant respiratory rates
in . lemaneiformis. however, for 25 grown . lactuca, the increment of co2
did not enhance the pn rates but rapidly decreased the rd rates itself.
with the higher rd pg ratios in . lemaneiformis than . lactuca, the
warming thereby promoted more allocation of photosynthetic products to
respiratory consumption in . lemaneiformis. both pg and rd rates exhibited
lower temperature acclimation in two seaweeds. in addition, elevated co2
markedly increased the relative growth rate and phycobiliprotein contents
at 25 , but exhibited no enhancement of chlorophyll , carotenoids ,
soluble carbohydrate , and soluble protein contents in . lemaneiformis,
with the reduction of sc when temperature increased only. we suggested
that climate changes were probably more benefit to . lactuca than to .
lemaneiformis, inherently justifying the metabolism during . lemaneiformis
maricultivation. 2018, springer verlag gmbh germany, part of springer
nature.
- text: >-
blue carbon is vital aspect of climate change mitigation, which
necessitates the identification of stocks and drivers for implementing
mitigation strategies. however, reclamation may be among the most invasive
forms, and the question of its influence has not been addressed well in
blue carbon research. therefore, the effects of reclamation on carbon
stocks and the interaction of crucial drivers from reclamation time areas
were evaluated in the liaohe river delta and compared with natural
reserves . carbon stocks based on invest model were lower than preexisting
conditions . one way analysis of variance showed that average carbon
stocks accumulated 55 years after reclamation and reached the lowest value
in 85 years. the interaction analysis of dominant drivers affecting carbon
showed the difference between reclaimed areas and reserves regarding
potential effect pathways. in the 1930s and 1960s reclamation time areas,
crop yield and industrial output determined blue carbon by changing no3
and ap. in the 1990s reclamation time area, population density played an
important role. in defining the impact of vegetation cover on carbon
within the reserves, the distance to the coast and residence were
significant factors. this study demonstrated that coastal
- text: >-
multiple techniques, including thermal infrared aerial remote sensing,
geophysical and geological data, geochemical characterization and radium
isotopes, were used to evaluate the role of groundwater as source of
dissolved nutrients, carbon, and trace gases to the okatee river estuary,
south carolina. thermal infrared aerial remote sensing surveys illustrated
the presence of multiple submarine groundwater discharge sites in okatee
headwaters. significant relationships were observed between groundwater
geochemical constituents and ra 226 activity in groundwater with higher ra
226 activity correlated to higher concentrations of organics, dissolved
inorganic carbon, nutrients, and trace gases to the okatee system. system
level radium mass balance confirmed substantial submarine groundwater
discharge contribution of these constituents to the okatee river.
diffusive benthic flux measurements and potential denitrification rate
assays tracked the fate of constituents in creek bank sediments. diffusive
benthic fluxes were substantially lower than calculated radium based
submarine groundwater discharge inputs, showing that advection of
groundwater derived nutrients dominated fluxes in the system. while
considerable potential for denitrification in tidal creek bank sediments
was noted, in situ denitrification rates were nitrate limited, making
intertidal sediments an inefficient nitrogen sink in this system.
groundwater geochemical data indicated significant differences in
groundwater chemical composition and radium activity ratios between the
eastern and western sides of the river; these likely arose from the
distinct hydrological regimes observed in each area. groundwater from the
western side of the okatee headwaters was characterized by higher
concentrations of dissolved organic and inorganic carbon, dissolved
organic nitrogen, inorganic nutrients and reduced metabolites and trace
gases, .. methane and nitrous oxide, than groundwater from the eastern
side. differences in microbial sulfate reduction, organic matter supply,
and or groundwater residence time likely contributed to this pattern. the
contrasting features of the east and west sub marsh zones highlight the
need for multiple techniques for characterization of submarine groundwater
discharge sources and the impact of biogeochemical processes on the
delivery of nutrients and carbon to coastal areas via submarine
groundwater discharge. 2014 elsevier ltd. all rights reserved.
- text: >-
blue carbon ecosystem initiatives in the coral triangle region are
increasing due to their amplified recognition in mitigating global climate
change. although transdisciplinary approaches in the blue carbon discourse
and collaborative actions are gaining momentum in the international and
national arenas, more work is still needed at the local level. the study
pursues how bce initiatives permeate through the local communities in the
philippines and indonesia, as part of ctr. using perception surveys, the
coastal residents from busuanga, philippines, and karimunjawa, indonesia
were interviewed on their awareness, utilization, perceived threats, and
management strategies for bces. potential factors affecting residents
perceptions were explored using multivariate regression and correlation
analyses. also, comparative analysis was done to determine distinctions
and commonalities in perceptions as influenced by site specific scenarios.
results show that, despite respondents presenting relatively high
awareness of bce services, levels of utilization are low with 42. 92. and
23. 85. respondents in busuanga and karimunjawa, respectively, not
directly utilizing bce resources. regression analysis showed that
respondents occupation significantly influenced their utilization rate and
observed opposite correlations in busuanga and karimunjawa . perceived
threats are found to be driven by personal experiences occurrence of
natural disasters in busuanga whereas discerned anthropogenic activities
in karimunjawa. meanwhile, recognized management strategies are influenced
by the strong presence of relevant agencies like non government and people
organizations in busuanga and the local government in karimunjawa. these
results can be translated as useful metrics in contextualizing and or
enhancing bce management plans specifically in strategizing advocacy
campaigns and engagement of local stakeholders across the ctr.
- text: >-
mangrove wetlands are important ecosystems, yet human development coupled
with climate change threatens mangroves and their large carbon stores.
this study seeks to understand the soil carbon dynamics in hydrologically
altered mangrove swamps by studying aboveground biomass estimates and
belowground soil carbon concentrations in mangrove swamps with high,
medium, and low levels of disturbance in catano, jobos bay, and vieques,
puerto rico. all three sites were affected by hurricane maria in 2017, one
year prior to the study. as result of being hit by the saffir simpson
category hurricane, the low disturbance site had almost no living
mangroves left during sampling. there was no correlation between level of
hydrologic alteration and carbon storage, rather different patterns
emerged for each of the three sites. at the highly disturbed location,
belowground carbon mass averaged .048 .001 cm which increased with
increased aboveground biomass. at the moderately disturbed location,
belowground carbon mass averaged .047 .003 cm and corresponded to distance
from open water. at the low disturbed location, organic carbon was
consistent between all sites and inorganic carbon concentrations
controlled total carbon mass which averaged .048 .002 cm. these results
suggest that mangroves are adaptive and resilient and have the potential
to retain their carbon storage capacities despite hydrologic alterations,
but mass carbon storage within mangrove forests can be spatially variable
in hydrologically altered conditions.
pipeline_tag: text-classification
inference: false
base_model: sentence-transformers/paraphrase-mpnet-base-v2
SetFit with sentence-transformers/paraphrase-mpnet-base-v2
This is a SetFit model that can be used for Text Classification. This SetFit model uses sentence-transformers/paraphrase-mpnet-base-v2 as the Sentence Transformer embedding model. A MultiOutputClassifier 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: sentence-transformers/paraphrase-mpnet-base-v2
- Classification head: a MultiOutputClassifier instance
- Maximum Sequence Length: 512 tokens
Model Sources
- Repository: SetFit on GitHub
- Paper: Efficient Few-Shot Learning Without Prompts
- Blogpost: SetFit: Efficient Few-Shot Learning Without Prompts
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("ignaciosg/blueCarbon")
# Run inference
preds = model("blue carbon is vital aspect of climate change mitigation, which necessitates the identification of stocks and drivers for implementing mitigation strategies. however, reclamation may be among the most invasive forms, and the question of its influence has not been addressed well in blue carbon research. therefore, the effects of reclamation on carbon stocks and the interaction of crucial drivers from reclamation time areas were evaluated in the liaohe river delta and compared with natural reserves . carbon stocks based on invest model were lower than preexisting conditions . one way analysis of variance showed that average carbon stocks accumulated 55 years after reclamation and reached the lowest value in 85 years. the interaction analysis of dominant drivers affecting carbon showed the difference between reclaimed areas and reserves regarding potential effect pathways. in the 1930s and 1960s reclamation time areas, crop yield and industrial output determined blue carbon by changing no3 and ap. in the 1990s reclamation time area, population density played an important role. in defining the impact of vegetation cover on carbon within the reserves, the distance to the coast and residence were significant factors. this study demonstrated that coastal")
Training Details
Training Set Metrics
Training set | Min | Median | Max |
---|---|---|---|
Word count | 105 | 229.475 | 432 |
Training Hyperparameters
- batch_size: (1, 1)
- num_epochs: (1, 1)
- max_steps: -1
- sampling_strategy: oversampling
- body_learning_rate: (2e-05, 1e-05)
- head_learning_rate: 0.0006155918397454662
- loss: CosineSimilarityLoss
- distance_metric: cosine_distance
- margin: 0.25
- end_to_end: False
- use_amp: False
- warmup_proportion: 0.1
- max_length: 1000
- seed: 42
- eval_max_steps: -1
- load_best_model_at_end: False
Training Results
Epoch | Step | Training Loss | Validation Loss |
---|---|---|---|
0.0000 | 1 | 0.1819 | - |
0.0011 | 50 | 0.201 | - |
0.0023 | 100 | 0.3533 | - |
0.0034 | 150 | 0.0788 | - |
0.0046 | 200 | 0.1445 | - |
0.0057 | 250 | 0.1584 | - |
0.0069 | 300 | 0.3425 | - |
0.0080 | 350 | 0.1203 | - |
0.0092 | 400 | 0.2045 | - |
0.0103 | 450 | 0.0287 | - |
0.0115 | 500 | 0.1784 | - |
0.0126 | 550 | 0.2521 | - |
0.0138 | 600 | 0.1285 | - |
0.0149 | 650 | 0.2292 | - |
0.0161 | 700 | 0.0943 | - |
0.0172 | 750 | 0.1753 | - |
0.0184 | 800 | 0.3433 | - |
0.0195 | 850 | 0.262 | - |
0.0207 | 900 | 0.1097 | - |
0.0218 | 950 | 0.0015 | - |
0.0230 | 1000 | 0.5522 | - |
0.0241 | 1050 | 0.5939 | - |
0.0253 | 1100 | 0.1134 | - |
0.0264 | 1150 | 0.1258 | - |
0.0276 | 1200 | 0.0146 | - |
0.0287 | 1250 | 0.0467 | - |
0.0299 | 1300 | 0.3501 | - |
0.0310 | 1350 | 0.291 | - |
0.0322 | 1400 | 0.0569 | - |
0.0333 | 1450 | 0.0812 | - |
0.0345 | 1500 | 0.3397 | - |
0.0356 | 1550 | 0.1664 | - |
0.0368 | 1600 | 0.3841 | - |
0.0379 | 1650 | 0.1659 | - |
0.0391 | 1700 | 0.0809 | - |
0.0402 | 1750 | 0.3604 | - |
0.0414 | 1800 | 0.0056 | - |
0.0425 | 1850 | 0.3335 | - |
0.0437 | 1900 | 0.0005 | - |
0.0448 | 1950 | 0.1624 | - |
0.0460 | 2000 | 0.8162 | - |
0.0471 | 2050 | 0.0097 | - |
0.0483 | 2100 | 0.2561 | - |
0.0494 | 2150 | 0.0003 | - |
0.0506 | 2200 | 0.4198 | - |
0.0517 | 2250 | 0.0002 | - |
0.0529 | 2300 | 0.2793 | - |
0.0540 | 2350 | 0.6288 | - |
0.0552 | 2400 | 0.6944 | - |
0.0563 | 2450 | 0.7394 | - |
0.0575 | 2500 | 0.011 | - |
0.0586 | 2550 | 0.8041 | - |
0.0598 | 2600 | 0.0041 | - |
0.0609 | 2650 | 0.2446 | - |
0.0621 | 2700 | 0.2759 | - |
0.0632 | 2750 | 0.151 | - |
0.0644 | 2800 | 0.0651 | - |
0.0655 | 2850 | 0.0026 | - |
0.0666 | 2900 | 0.0845 | - |
0.0678 | 2950 | 0.7541 | - |
0.0689 | 3000 | 0.0993 | - |
0.0701 | 3050 | 0.7355 | - |
0.0712 | 3100 | 0.6959 | - |
0.0724 | 3150 | 0.1687 | - |
0.0735 | 3200 | 0.2048 | - |
0.0747 | 3250 | 0.0906 | - |
0.0758 | 3300 | 0.0582 | - |
0.0770 | 3350 | 0.9064 | - |
0.0781 | 3400 | 0.8038 | - |
0.0793 | 3450 | 0.2515 | - |
0.0804 | 3500 | 0.0196 | - |
0.0816 | 3550 | 0.0081 | - |
0.0827 | 3600 | 0.8483 | - |
0.0839 | 3650 | 0.0651 | - |
0.0850 | 3700 | 0.8224 | - |
0.0862 | 3750 | 0.2872 | - |
0.0873 | 3800 | 0.0506 | - |
0.0885 | 3850 | 0.6795 | - |
0.0896 | 3900 | 0.0126 | - |
0.0908 | 3950 | 0.5083 | - |
0.0919 | 4000 | 0.0215 | - |
0.0931 | 4050 | 0.8133 | - |
0.0942 | 4100 | 0.1534 | - |
0.0954 | 4150 | 0.2397 | - |
0.0965 | 4200 | 0.8576 | - |
0.0977 | 4250 | 0.0554 | - |
0.0988 | 4300 | 0.1018 | - |
0.1000 | 4350 | 0.3324 | - |
0.1011 | 4400 | 0.0221 | - |
0.1023 | 4450 | 0.0516 | - |
0.1034 | 4500 | 0.796 | - |
0.1046 | 4550 | 0.0903 | - |
0.1057 | 4600 | 0.1979 | - |
0.1069 | 4650 | 0.9194 | - |
0.1080 | 4700 | 0.2556 | - |
0.1092 | 4750 | 0.7224 | - |
0.1103 | 4800 | 0.0012 | - |
0.1115 | 4850 | 0.5042 | - |
0.1126 | 4900 | 0.5732 | - |
0.1138 | 4950 | 0.1041 | - |
0.1149 | 5000 | 0.0247 | - |
0.1161 | 5050 | 0.0265 | - |
0.1172 | 5100 | 0.0126 | - |
0.1184 | 5150 | 0.0098 | - |
0.1195 | 5200 | 0.0386 | - |
0.1207 | 5250 | 0.001 | - |
0.1218 | 5300 | 0.9248 | - |
0.1230 | 5350 | 0.4783 | - |
0.1241 | 5400 | 0.1841 | - |
0.1253 | 5450 | 0.4721 | - |
0.1264 | 5500 | 0.0601 | - |
0.1276 | 5550 | 0.0073 | - |
0.1287 | 5600 | 0.0028 | - |
0.1298 | 5650 | 0.012 | - |
0.1310 | 5700 | 0.0451 | - |
0.1321 | 5750 | 0.0125 | - |
0.1333 | 5800 | 0.5423 | - |
0.1344 | 5850 | 0.7545 | - |
0.1356 | 5900 | 0.0158 | - |
0.1367 | 5950 | 0.1388 | - |
0.1379 | 6000 | 0.0136 | - |
0.1390 | 6050 | 0.0043 | - |
0.1402 | 6100 | 0.4147 | - |
0.1413 | 6150 | 0.0503 | - |
0.1425 | 6200 | 0.0347 | - |
0.1436 | 6250 | 0.0465 | - |
0.1448 | 6300 | 0.0086 | - |
0.1459 | 6350 | 0.8752 | - |
0.1471 | 6400 | 0.5546 | - |
0.1482 | 6450 | 0.0348 | - |
0.1494 | 6500 | 0.0853 | - |
0.1505 | 6550 | 0.6107 | - |
0.1517 | 6600 | 0.005 | - |
0.1528 | 6650 | 0.3526 | - |
0.1540 | 6700 | 0.2429 | - |
0.1551 | 6750 | 0.6727 | - |
0.1563 | 6800 | 0.0019 | - |
0.1574 | 6850 | 0.6662 | - |
0.1586 | 6900 | 0.0068 | - |
0.1597 | 6950 | 0.0117 | - |
0.1609 | 7000 | 0.4718 | - |
0.1620 | 7050 | 0.0072 | - |
0.1632 | 7100 | 0.8174 | - |
0.1643 | 7150 | 0.0094 | - |
0.1655 | 7200 | 0.0241 | - |
0.1666 | 7250 | 0.1359 | - |
0.1678 | 7300 | 0.0528 | - |
0.1689 | 7350 | 0.0184 | - |
0.1701 | 7400 | 0.2204 | - |
0.1712 | 7450 | 0.3476 | - |
0.1724 | 7500 | 0.1153 | - |
0.1735 | 7550 | 0.0717 | - |
0.1747 | 7600 | 0.022 | - |
0.1758 | 7650 | 0.0311 | - |
0.1770 | 7700 | 0.4385 | - |
0.1781 | 7750 | 0.4274 | - |
0.1793 | 7800 | 0.4994 | - |
0.1804 | 7850 | 0.2518 | - |
0.1816 | 7900 | 0.8652 | - |
0.1827 | 7950 | 0.0019 | - |
0.1839 | 8000 | 0.01 | - |
0.1850 | 8050 | 0.0129 | - |
0.1862 | 8100 | 0.0001 | - |
0.1873 | 8150 | 0.0005 | - |
0.1885 | 8200 | 0.0199 | - |
0.1896 | 8250 | 0.1489 | - |
0.1908 | 8300 | 0.0016 | - |
0.1919 | 8350 | 0.5111 | - |
0.1931 | 8400 | 0.807 | - |
0.1942 | 8450 | 0.1489 | - |
0.1953 | 8500 | 0.29 | - |
0.1965 | 8550 | 0.0001 | - |
0.1976 | 8600 | 0.0043 | - |
0.1988 | 8650 | 0.0041 | - |
0.1999 | 8700 | 0.3061 | - |
0.2011 | 8750 | 0.0221 | - |
0.2022 | 8800 | 0.801 | - |
0.2034 | 8850 | 0.2316 | - |
0.2045 | 8900 | 0.2784 | - |
0.2057 | 8950 | 0.0957 | - |
0.2068 | 9000 | 0.611 | - |
0.2080 | 9050 | 0.7529 | - |
0.2091 | 9100 | 0.0565 | - |
0.2103 | 9150 | 0.0114 | - |
0.2114 | 9200 | 0.2864 | - |
0.2126 | 9250 | 0.1954 | - |
0.2137 | 9300 | 0.7993 | - |
0.2149 | 9350 | 0.0501 | - |
0.2160 | 9400 | 0.0051 | - |
0.2172 | 9450 | 0.6012 | - |
0.2183 | 9500 | 0.0131 | - |
0.2195 | 9550 | 0.0157 | - |
0.2206 | 9600 | 0.0606 | - |
0.2218 | 9650 | 0.9143 | - |
0.2229 | 9700 | 0.0001 | - |
0.2241 | 9750 | 0.0021 | - |
0.2252 | 9800 | 0.0004 | - |
0.2264 | 9850 | 0.0498 | - |
0.2275 | 9900 | 0.0021 | - |
0.2287 | 9950 | 0.8591 | - |
0.2298 | 10000 | 0.2218 | - |
0.2310 | 10050 | 0.0065 | - |
0.2321 | 10100 | 0.0924 | - |
0.2333 | 10150 | 0.8866 | - |
0.2344 | 10200 | 0.0004 | - |
0.2356 | 10250 | 0.1434 | - |
0.2367 | 10300 | 0.0118 | - |
0.2379 | 10350 | 0.025 | - |
0.2390 | 10400 | 0.8472 | - |
0.2402 | 10450 | 0.0352 | - |
0.2413 | 10500 | 0.0105 | - |
0.2425 | 10550 | 0.0025 | - |
0.2436 | 10600 | 0.0042 | - |
0.2448 | 10650 | 0.3461 | - |
0.2459 | 10700 | 0.0314 | - |
0.2471 | 10750 | 0.1411 | - |
0.2482 | 10800 | 0.0006 | - |
0.2494 | 10850 | 0.0013 | - |
0.2505 | 10900 | 0.894 | - |
0.2517 | 10950 | 0.9961 | - |
0.2528 | 11000 | 0.9908 | - |
0.2540 | 11050 | 0.836 | - |
0.2551 | 11100 | 0.8847 | - |
0.2563 | 11150 | 0.8493 | - |
0.2574 | 11200 | 0.5851 | - |
0.2585 | 11250 | 0.9502 | - |
0.2597 | 11300 | 0.8396 | - |
0.2608 | 11350 | 0.1942 | - |
0.2620 | 11400 | 0.9298 | - |
0.2631 | 11450 | 0.742 | - |
0.2643 | 11500 | 0.8624 | - |
0.2654 | 11550 | 0.5423 | - |
0.2666 | 11600 | 0.8576 | - |
0.2677 | 11650 | 0.8042 | - |
0.2689 | 11700 | 0.7447 | - |
0.2700 | 11750 | 0.5319 | - |
0.2712 | 11800 | 0.451 | - |
0.2723 | 11850 | 0.4115 | - |
0.2735 | 11900 | 0.6772 | - |
0.2746 | 11950 | 0.4701 | - |
0.2758 | 12000 | 0.6101 | - |
0.2769 | 12050 | 0.4914 | - |
0.2781 | 12100 | 0.653 | - |
0.2792 | 12150 | 0.6205 | - |
0.2804 | 12200 | 0.651 | - |
0.2815 | 12250 | 0.2223 | - |
0.2827 | 12300 | 0.7124 | - |
0.2838 | 12350 | 0.6502 | - |
0.2850 | 12400 | 0.5812 | - |
0.2861 | 12450 | 0.6483 | - |
0.2873 | 12500 | 0.7335 | - |
0.2884 | 12550 | 0.239 | - |
0.2896 | 12600 | 0.6499 | - |
0.2907 | 12650 | 0.4453 | - |
0.2919 | 12700 | 0.7152 | - |
0.2930 | 12750 | 0.5551 | - |
0.2942 | 12800 | 0.6034 | - |
0.2953 | 12850 | 0.5714 | - |
0.2965 | 12900 | 0.5867 | - |
0.2976 | 12950 | 0.4249 | - |
0.2988 | 13000 | 0.7262 | - |
0.2999 | 13050 | 0.542 | - |
0.3011 | 13100 | 0.5301 | - |
0.3022 | 13150 | 0.7503 | - |
0.3034 | 13200 | 0.6918 | - |
0.3045 | 13250 | 0.5352 | - |
0.3057 | 13300 | 0.6065 | - |
0.3068 | 13350 | 0.373 | - |
0.3080 | 13400 | 0.7648 | - |
0.3091 | 13450 | 0.2762 | - |
0.3103 | 13500 | 0.708 | - |
0.3114 | 13550 | 0.1481 | - |
0.3126 | 13600 | 0.7231 | - |
0.3137 | 13650 | 0.6023 | - |
0.3149 | 13700 | 0.7021 | - |
0.3160 | 13750 | 0.5843 | - |
0.3172 | 13800 | 0.7361 | - |
0.3183 | 13850 | 0.7844 | - |
0.3195 | 13900 | 0.51 | - |
0.3206 | 13950 | 0.506 | - |
0.3218 | 14000 | 0.3072 | - |
0.3229 | 14050 | 0.5854 | - |
0.3240 | 14100 | 0.3553 | - |
0.3252 | 14150 | 0.6827 | - |
0.3263 | 14200 | 0.5342 | - |
0.3275 | 14250 | 0.6887 | - |
0.3286 | 14300 | 0.6007 | - |
0.3298 | 14350 | 0.4573 | - |
0.3309 | 14400 | 0.5979 | - |
0.3321 | 14450 | 0.5328 | - |
0.3332 | 14500 | 0.6814 | - |
0.3344 | 14550 | 0.6207 | - |
0.3355 | 14600 | 0.8189 | - |
0.3367 | 14650 | 0.5794 | - |
0.3378 | 14700 | 0.3987 | - |
0.3390 | 14750 | 0.5281 | - |
0.3401 | 14800 | 0.652 | - |
0.3413 | 14850 | 0.6811 | - |
0.3424 | 14900 | 0.3334 | - |
0.3436 | 14950 | 0.565 | - |
0.3447 | 15000 | 0.4956 | - |
0.3459 | 15050 | 0.7289 | - |
0.3470 | 15100 | 0.6103 | - |
0.3482 | 15150 | 0.4173 | - |
0.3493 | 15200 | 0.2138 | - |
0.3505 | 15250 | 0.893 | - |
0.3516 | 15300 | 0.5385 | - |
0.3528 | 15350 | 0.6386 | - |
0.3539 | 15400 | 0.7168 | - |
0.3551 | 15450 | 0.1189 | - |
0.3562 | 15500 | 0.3046 | - |
0.3574 | 15550 | 0.4776 | - |
0.3585 | 15600 | 0.7062 | - |
0.3597 | 15650 | 0.0972 | - |
0.3608 | 15700 | 0.4485 | - |
0.3620 | 15750 | 0.5843 | - |
0.3631 | 15800 | 0.5656 | - |
0.3643 | 15850 | 0.5682 | - |
0.3654 | 15900 | 0.416 | - |
0.3666 | 15950 | 0.2427 | - |
0.3677 | 16000 | 0.4942 | - |
0.3689 | 16050 | 0.4734 | - |
0.3700 | 16100 | 0.7099 | - |
0.3712 | 16150 | 0.5899 | - |
0.3723 | 16200 | 0.3502 | - |
0.3735 | 16250 | 0.3448 | - |
0.3746 | 16300 | 0.6606 | - |
0.3758 | 16350 | 0.5239 | - |
0.3769 | 16400 | 0.6872 | - |
0.3781 | 16450 | 0.2828 | - |
0.3792 | 16500 | 0.6973 | - |
0.3804 | 16550 | 0.6628 | - |
0.3815 | 16600 | 0.6429 | - |
0.3827 | 16650 | 0.4321 | - |
0.3838 | 16700 | 0.6626 | - |
0.3850 | 16750 | 0.5044 | - |
0.3861 | 16800 | 0.7683 | - |
0.3872 | 16850 | 0.6687 | - |
0.3884 | 16900 | 0.5821 | - |
0.3895 | 16950 | 0.6572 | - |
0.3907 | 17000 | 0.9609 | - |
0.3918 | 17050 | 0.0123 | - |
0.3930 | 17100 | 0.5649 | - |
0.3941 | 17150 | 0.1006 | - |
0.3953 | 17200 | 0.003 | - |
0.3964 | 17250 | 0.278 | - |
0.3976 | 17300 | 0.8632 | - |
0.3987 | 17350 | 0.5101 | - |
0.3999 | 17400 | 0.8753 | - |
0.4010 | 17450 | 0.3195 | - |
0.4022 | 17500 | 0.9436 | - |
0.4033 | 17550 | 0.9388 | - |
0.4045 | 17600 | 0.0097 | - |
0.4056 | 17650 | 0.6898 | - |
0.4068 | 17700 | 0.035 | - |
0.4079 | 17750 | 0.4828 | - |
0.4091 | 17800 | 0.1888 | - |
0.4102 | 17850 | 0.0354 | - |
0.4114 | 17900 | 0.0008 | - |
0.4125 | 17950 | 0.2885 | - |
0.4137 | 18000 | 0.0624 | - |
0.4148 | 18050 | 0.5545 | - |
0.4160 | 18100 | 0.5317 | - |
0.4171 | 18150 | 0.0207 | - |
0.4183 | 18200 | 0.0228 | - |
0.4194 | 18250 | 0.0168 | - |
0.4206 | 18300 | 0.0935 | - |
0.4217 | 18350 | 0.8391 | - |
0.4229 | 18400 | 0.0005 | - |
0.4240 | 18450 | 0.7018 | - |
0.4252 | 18500 | 0.0137 | - |
0.4263 | 18550 | 0.0053 | - |
0.4275 | 18600 | 0.0307 | - |
0.4286 | 18650 | 0.0127 | - |
0.4298 | 18700 | 0.2351 | - |
0.4309 | 18750 | 0.0047 | - |
0.4321 | 18800 | 0.0114 | - |
0.4332 | 18850 | 0.0153 | - |
0.4344 | 18900 | 0.3732 | - |
0.4355 | 18950 | 0.77 | - |
0.4367 | 19000 | 0.1298 | - |
0.4378 | 19050 | 0.7064 | - |
0.4390 | 19100 | 0.0 | - |
0.4401 | 19150 | 0.0044 | - |
0.4413 | 19200 | 0.7627 | - |
0.4424 | 19250 | 0.556 | - |
0.4436 | 19300 | 0.2105 | - |
0.4447 | 19350 | 0.8194 | - |
0.4459 | 19400 | 0.027 | - |
0.4470 | 19450 | 0.9308 | - |
0.4482 | 19500 | 0.0194 | - |
0.4493 | 19550 | 0.0144 | - |
0.4505 | 19600 | 0.584 | - |
0.4516 | 19650 | 0.0042 | - |
0.4527 | 19700 | 0.1354 | - |
0.4539 | 19750 | 0.2151 | - |
0.4550 | 19800 | 0.0006 | - |
0.4562 | 19850 | 0.3085 | - |
0.4573 | 19900 | 0.0543 | - |
0.4585 | 19950 | 0.0178 | - |
0.4596 | 20000 | 0.418 | - |
0.4608 | 20050 | 0.019 | - |
0.4619 | 20100 | 0.0001 | - |
0.4631 | 20150 | 0.5443 | - |
0.4642 | 20200 | 0.5111 | - |
0.4654 | 20250 | 0.0594 | - |
0.4665 | 20300 | 0.0086 | - |
0.4677 | 20350 | 0.0064 | - |
0.4688 | 20400 | 0.0577 | - |
0.4700 | 20450 | 0.0712 | - |
0.4711 | 20500 | 0.0271 | - |
0.4723 | 20550 | 0.5118 | - |
0.4734 | 20600 | 0.1834 | - |
0.4746 | 20650 | 0.0116 | - |
0.4757 | 20700 | 0.0052 | - |
0.4769 | 20750 | 0.7975 | - |
0.4780 | 20800 | 0.3037 | - |
0.4792 | 20850 | 0.0264 | - |
0.4803 | 20900 | 0.6911 | - |
0.4815 | 20950 | 0.008 | - |
0.4826 | 21000 | 0.0041 | - |
0.4838 | 21050 | 0.0379 | - |
0.4849 | 21100 | 0.0033 | - |
0.4861 | 21150 | 0.0297 | - |
0.4872 | 21200 | 0.0147 | - |
0.4884 | 21250 | 0.0001 | - |
0.4895 | 21300 | 0.0047 | - |
0.4907 | 21350 | 0.0247 | - |
0.4918 | 21400 | 0.0059 | - |
0.4930 | 21450 | 0.5724 | - |
0.4941 | 21500 | 0.3113 | - |
0.4953 | 21550 | 0.0026 | - |
0.4964 | 21600 | 0.835 | - |
0.4976 | 21650 | 0.0007 | - |
0.4987 | 21700 | 0.029 | - |
0.4999 | 21750 | 0.707 | - |
0.5010 | 21800 | 0.0211 | - |
0.5022 | 21850 | 0.0071 | - |
0.5033 | 21900 | 0.0009 | - |
0.5045 | 21950 | 0.0319 | - |
0.5056 | 22000 | 0.2219 | - |
0.5068 | 22050 | 0.0244 | - |
0.5079 | 22100 | 0.0341 | - |
0.5091 | 22150 | 0.0372 | - |
0.5102 | 22200 | 0.3981 | - |
0.5114 | 22250 | 0.0627 | - |
0.5125 | 22300 | 0.0559 | - |
0.5137 | 22350 | 0.5366 | - |
0.5148 | 22400 | 0.6952 | - |
0.5159 | 22450 | 0.0504 | - |
0.5171 | 22500 | 0.5098 | - |
0.5182 | 22550 | 0.6538 | - |
0.5194 | 22600 | 0.0015 | - |
0.5205 | 22650 | 0.0005 | - |
0.5217 | 22700 | 0.0974 | - |
0.5228 | 22750 | 0.009 | - |
0.5240 | 22800 | 0.6559 | - |
0.5251 | 22850 | 0.026 | - |
0.5263 | 22900 | 0.0049 | - |
0.5274 | 22950 | 0.0104 | - |
0.5286 | 23000 | 0.7918 | - |
0.5297 | 23050 | 0.0007 | - |
0.5309 | 23100 | 0.0015 | - |
0.5320 | 23150 | 0.2873 | - |
0.5332 | 23200 | 0.002 | - |
0.5343 | 23250 | 0.0067 | - |
0.5355 | 23300 | 0.2943 | - |
0.5366 | 23350 | 0.0029 | - |
0.5378 | 23400 | 0.0 | - |
0.5389 | 23450 | 0.0727 | - |
0.5401 | 23500 | 0.0084 | - |
0.5412 | 23550 | 0.0 | - |
0.5424 | 23600 | 0.0054 | - |
0.5435 | 23650 | 0.0004 | - |
0.5447 | 23700 | 0.5525 | - |
0.5458 | 23750 | 0.0251 | - |
0.5470 | 23800 | 0.0269 | - |
0.5481 | 23850 | 0.7426 | - |
0.5493 | 23900 | 0.0016 | - |
0.5504 | 23950 | 0.8143 | - |
0.5516 | 24000 | 0.5158 | - |
0.5527 | 24050 | 0.0047 | - |
0.5539 | 24100 | 0.0067 | - |
0.5550 | 24150 | 0.0 | - |
0.5562 | 24200 | 0.0045 | - |
0.5573 | 24250 | 0.0021 | - |
0.5585 | 24300 | 0.0012 | - |
0.5596 | 24350 | 0.3501 | - |
0.5608 | 24400 | 0.0101 | - |
0.5619 | 24450 | 0.0008 | - |
0.5631 | 24500 | 0.0112 | - |
0.5642 | 24550 | 0.0148 | - |
0.5654 | 24600 | 0.2246 | - |
0.5665 | 24650 | 0.1538 | - |
0.5677 | 24700 | 0.0001 | - |
0.5688 | 24750 | 0.0001 | - |
0.5700 | 24800 | 0.1296 | - |
0.5711 | 24850 | 0.0101 | - |
0.5723 | 24900 | 0.0032 | - |
0.5734 | 24950 | 0.0714 | - |
0.5746 | 25000 | 0.0 | - |
0.5757 | 25050 | 0.0886 | - |
0.5769 | 25100 | 0.0003 | - |
0.5780 | 25150 | 0.0041 | - |
0.5792 | 25200 | 0.0151 | - |
0.5803 | 25250 | 0.0099 | - |
0.5814 | 25300 | 0.0008 | - |
0.5826 | 25350 | 0.028 | - |
0.5837 | 25400 | 0.1064 | - |
0.5849 | 25450 | 0.0373 | - |
0.5860 | 25500 | 0.5589 | - |
0.5872 | 25550 | 0.2522 | - |
0.5883 | 25600 | 0.8553 | - |
0.5895 | 25650 | 0.0004 | - |
0.5906 | 25700 | 0.6575 | - |
0.5918 | 25750 | 0.0034 | - |
0.5929 | 25800 | 0.7313 | - |
0.5941 | 25850 | 0.8363 | - |
0.5952 | 25900 | 0.0156 | - |
0.5964 | 25950 | 0.0044 | - |
0.5975 | 26000 | 0.1387 | - |
0.5987 | 26050 | 0.0487 | - |
0.5998 | 26100 | 0.001 | - |
0.6010 | 26150 | 0.0004 | - |
0.6021 | 26200 | 0.0071 | - |
0.6033 | 26250 | 0.0012 | - |
0.6044 | 26300 | 0.021 | - |
0.6056 | 26350 | 0.0212 | - |
0.6067 | 26400 | 0.8472 | - |
0.6079 | 26450 | 0.5686 | - |
0.6090 | 26500 | 0.0721 | - |
0.6102 | 26550 | 0.0235 | - |
0.6113 | 26600 | 0.0 | - |
0.6125 | 26650 | 0.0098 | - |
0.6136 | 26700 | 0.3805 | - |
0.6148 | 26750 | 0.0525 | - |
0.6159 | 26800 | 0.0139 | - |
0.6171 | 26850 | 0.0011 | - |
0.6182 | 26900 | 0.0013 | - |
0.6194 | 26950 | 0.0058 | - |
0.6205 | 27000 | 0.0581 | - |
0.6217 | 27050 | 0.477 | - |
0.6228 | 27100 | 0.0073 | - |
0.6240 | 27150 | 0.0033 | - |
0.6251 | 27200 | 0.0082 | - |
0.6263 | 27250 | 0.0028 | - |
0.6274 | 27300 | 0.0001 | - |
0.6286 | 27350 | 0.0265 | - |
0.6297 | 27400 | 0.097 | - |
0.6309 | 27450 | 0.2339 | - |
0.6320 | 27500 | 0.5429 | - |
0.6332 | 27550 | 0.3859 | - |
0.6343 | 27600 | 0.0116 | - |
0.6355 | 27650 | 0.0006 | - |
0.6366 | 27700 | 0.0018 | - |
0.6378 | 27750 | 0.0197 | - |
0.6389 | 27800 | 0.0085 | - |
0.6401 | 27850 | 0.0 | - |
0.6412 | 27900 | 0.0141 | - |
0.6424 | 27950 | 0.1121 | - |
0.6435 | 28000 | 0.0123 | - |
0.6446 | 28050 | 0.3018 | - |
0.6458 | 28100 | 0.7669 | - |
0.6469 | 28150 | 0.6745 | - |
0.6481 | 28200 | 0.4283 | - |
0.6492 | 28250 | 0.0237 | - |
0.6504 | 28300 | 0.8327 | - |
0.6515 | 28350 | 0.1052 | - |
0.6527 | 28400 | 0.4264 | - |
0.6538 | 28450 | 0.6714 | - |
0.6550 | 28500 | 0.0039 | - |
0.6561 | 28550 | 0.0065 | - |
0.6573 | 28600 | 0.0178 | - |
0.6584 | 28650 | 0.3817 | - |
0.6596 | 28700 | 0.0584 | - |
0.6607 | 28750 | 0.0217 | - |
0.6619 | 28800 | 0.0019 | - |
0.6630 | 28850 | 0.4605 | - |
0.6642 | 28900 | 0.0049 | - |
0.6653 | 28950 | 0.0011 | - |
0.6665 | 29000 | 0.569 | - |
0.6676 | 29050 | 0.0 | - |
0.6688 | 29100 | 0.0874 | - |
0.6699 | 29150 | 0.5388 | - |
0.6711 | 29200 | 0.4093 | - |
0.6722 | 29250 | 0.3076 | - |
0.6734 | 29300 | 0.4542 | - |
0.6745 | 29350 | 0.2569 | - |
0.6757 | 29400 | 0.0155 | - |
0.6768 | 29450 | 0.1146 | - |
0.6780 | 29500 | 0.1341 | - |
0.6791 | 29550 | 0.0304 | - |
0.6803 | 29600 | 0.0095 | - |
0.6814 | 29650 | 0.443 | - |
0.6826 | 29700 | 0.5068 | - |
0.6837 | 29750 | 0.024 | - |
0.6849 | 29800 | 0.0079 | - |
0.6860 | 29850 | 0.1769 | - |
0.6872 | 29900 | 0.0001 | - |
0.6883 | 29950 | 0.0104 | - |
0.6895 | 30000 | 0.4234 | - |
0.6906 | 30050 | 0.0042 | - |
0.6918 | 30100 | 0.3934 | - |
0.6929 | 30150 | 0.0119 | - |
0.6941 | 30200 | 0.0012 | - |
0.6952 | 30250 | 0.4434 | - |
0.6964 | 30300 | 0.6101 | - |
0.6975 | 30350 | 0.3655 | - |
0.6987 | 30400 | 0.168 | - |
0.6998 | 30450 | 0.8202 | - |
0.7010 | 30500 | 0.0906 | - |
0.7021 | 30550 | 0.0287 | - |
0.7033 | 30600 | 0.3671 | - |
0.7044 | 30650 | 0.7084 | - |
0.7056 | 30700 | 0.3632 | - |
0.7067 | 30750 | 0.0027 | - |
0.7079 | 30800 | 0.0451 | - |
0.7090 | 30850 | 0.3421 | - |
0.7101 | 30900 | 0.0077 | - |
0.7113 | 30950 | 0.0404 | - |
0.7124 | 31000 | 0.7512 | - |
0.7136 | 31050 | 0.2898 | - |
0.7147 | 31100 | 0.0721 | - |
0.7159 | 31150 | 0.009 | - |
0.7170 | 31200 | 0.0474 | - |
0.7182 | 31250 | 0.0041 | - |
0.7193 | 31300 | 0.0249 | - |
0.7205 | 31350 | 0.3519 | - |
0.7216 | 31400 | 0.0936 | - |
0.7228 | 31450 | 0.0049 | - |
0.7239 | 31500 | 0.0035 | - |
0.7251 | 31550 | 0.0296 | - |
0.7262 | 31600 | 0.0264 | - |
0.7274 | 31650 | 0.5318 | - |
0.7285 | 31700 | 0.0029 | - |
0.7297 | 31750 | 0.7741 | - |
0.7308 | 31800 | 0.0807 | - |
0.7320 | 31850 | 0.0154 | - |
0.7331 | 31900 | 0.0181 | - |
0.7343 | 31950 | 0.7881 | - |
0.7354 | 32000 | 0.2723 | - |
0.7366 | 32050 | 0.0549 | - |
0.7377 | 32100 | 0.0198 | - |
0.7389 | 32150 | 0.0083 | - |
0.7400 | 32200 | 0.4985 | - |
0.7412 | 32250 | 0.0111 | - |
0.7423 | 32300 | 0.0057 | - |
0.7435 | 32350 | 0.0393 | - |
0.7446 | 32400 | 0.0786 | - |
0.7458 | 32450 | 0.1888 | - |
0.7469 | 32500 | 0.0382 | - |
0.7481 | 32550 | 0.5611 | - |
0.7492 | 32600 | 0.0749 | - |
0.7504 | 32650 | 0.0064 | - |
0.7515 | 32700 | 0.0002 | - |
0.7527 | 32750 | 0.0159 | - |
0.7538 | 32800 | 0.025 | - |
0.7550 | 32850 | 0.0271 | - |
0.7561 | 32900 | 0.251 | - |
0.7573 | 32950 | 0.0002 | - |
0.7584 | 33000 | 0.1407 | - |
0.7596 | 33050 | 0.1596 | - |
0.7607 | 33100 | 0.0069 | - |
0.7619 | 33150 | 0.0655 | - |
0.7630 | 33200 | 0.0435 | - |
0.7642 | 33250 | 0.0032 | - |
0.7653 | 33300 | 0.1908 | - |
0.7665 | 33350 | 0.4326 | - |
0.7676 | 33400 | 0.1699 | - |
0.7688 | 33450 | 0.005 | - |
0.7699 | 33500 | 0.4937 | - |
0.7711 | 33550 | 0.0635 | - |
0.7722 | 33600 | 0.0042 | - |
0.7733 | 33650 | 0.0001 | - |
0.7745 | 33700 | 0.0088 | - |
0.7756 | 33750 | 0.0313 | - |
0.7768 | 33800 | 0.0072 | - |
0.7779 | 33850 | 0.0291 | - |
0.7791 | 33900 | 0.0037 | - |
0.7802 | 33950 | 0.0192 | - |
0.7814 | 34000 | 0.0017 | - |
0.7825 | 34050 | 0.0006 | - |
0.7837 | 34100 | 0.0119 | - |
0.7848 | 34150 | 0.1647 | - |
0.7860 | 34200 | 0.009 | - |
0.7871 | 34250 | 0.0004 | - |
0.7883 | 34300 | 0.5268 | - |
0.7894 | 34350 | 0.0523 | - |
0.7906 | 34400 | 0.0537 | - |
0.7917 | 34450 | 0.1654 | - |
0.7929 | 34500 | 0.0003 | - |
0.7940 | 34550 | 0.0021 | - |
0.7952 | 34600 | 0.0016 | - |
0.7963 | 34650 | 0.0002 | - |
0.7975 | 34700 | 0.0001 | - |
0.7986 | 34750 | 0.0001 | - |
0.7998 | 34800 | 0.0204 | - |
0.8009 | 34850 | 0.0047 | - |
0.8021 | 34900 | 0.2942 | - |
0.8032 | 34950 | 0.0039 | - |
0.8044 | 35000 | 0.0237 | - |
0.8055 | 35050 | 0.0002 | - |
0.8067 | 35100 | 0.0009 | - |
0.8078 | 35150 | 0.7804 | - |
0.8090 | 35200 | 0.0012 | - |
0.8101 | 35250 | 0.0303 | - |
0.8113 | 35300 | 0.0265 | - |
0.8124 | 35350 | 0.0071 | - |
0.8136 | 35400 | 0.0053 | - |
0.8147 | 35450 | 0.068 | - |
0.8159 | 35500 | 0.0233 | - |
0.8170 | 35550 | 0.4748 | - |
0.8182 | 35600 | 0.0253 | - |
0.8193 | 35650 | 0.0 | - |
0.8205 | 35700 | 0.2029 | - |
0.8216 | 35750 | 0.0063 | - |
0.8228 | 35800 | 0.0179 | - |
0.8239 | 35850 | 0.0039 | - |
0.8251 | 35900 | 0.0123 | - |
0.8262 | 35950 | 0.3021 | - |
0.8274 | 36000 | 0.0096 | - |
0.8285 | 36050 | 0.3735 | - |
0.8297 | 36100 | 0.0281 | - |
0.8308 | 36150 | 0.0612 | - |
0.8320 | 36200 | 0.028 | - |
0.8331 | 36250 | 0.6296 | - |
0.8343 | 36300 | 0.1161 | - |
0.8354 | 36350 | 0.0249 | - |
0.8366 | 36400 | 0.0 | - |
0.8377 | 36450 | 0.4144 | - |
0.8388 | 36500 | 0.1574 | - |
0.8400 | 36550 | 0.0083 | - |
0.8411 | 36600 | 0.0385 | - |
0.8423 | 36650 | 0.4681 | - |
0.8434 | 36700 | 0.0628 | - |
0.8446 | 36750 | 0.0005 | - |
0.8457 | 36800 | 0.2092 | - |
0.8469 | 36850 | 0.009 | - |
0.8480 | 36900 | 0.031 | - |
0.8492 | 36950 | 0.3659 | - |
0.8503 | 37000 | 0.0003 | - |
0.8515 | 37050 | 0.0117 | - |
0.8526 | 37100 | 0.0061 | - |
0.8538 | 37150 | 0.0163 | - |
0.8549 | 37200 | 0.0 | - |
0.8561 | 37250 | 0.0668 | - |
0.8572 | 37300 | 0.0108 | - |
0.8584 | 37350 | 0.1344 | - |
0.8595 | 37400 | 0.0196 | - |
0.8607 | 37450 | 0.0006 | - |
0.8618 | 37500 | 0.0005 | - |
0.8630 | 37550 | 0.45 | - |
0.8641 | 37600 | 0.0002 | - |
0.8653 | 37650 | 0.0032 | - |
0.8664 | 37700 | 0.0035 | - |
0.8676 | 37750 | 0.1411 | - |
0.8687 | 37800 | 0.007 | - |
0.8699 | 37850 | 0.0015 | - |
0.8710 | 37900 | 0.6745 | - |
0.8722 | 37950 | 0.0002 | - |
0.8733 | 38000 | 0.2138 | - |
0.8745 | 38050 | 0.0092 | - |
0.8756 | 38100 | 0.4335 | - |
0.8768 | 38150 | 0.0011 | - |
0.8779 | 38200 | 0.0265 | - |
0.8791 | 38250 | 0.6394 | - |
0.8802 | 38300 | 0.3108 | - |
0.8814 | 38350 | 0.1918 | - |
0.8825 | 38400 | 0.0006 | - |
0.8837 | 38450 | 0.0075 | - |
0.8848 | 38500 | 0.5738 | - |
0.8860 | 38550 | 0.008 | - |
0.8871 | 38600 | 0.0043 | - |
0.8883 | 38650 | 0.7087 | - |
0.8894 | 38700 | 0.0044 | - |
0.8906 | 38750 | 0.0045 | - |
0.8917 | 38800 | 0.0009 | - |
0.8929 | 38850 | 0.0118 | - |
0.8940 | 38900 | 0.2812 | - |
0.8952 | 38950 | 0.0581 | - |
0.8963 | 39000 | 0.0016 | - |
0.8975 | 39050 | 0.0284 | - |
0.8986 | 39100 | 0.0061 | - |
0.8998 | 39150 | 0.13 | - |
0.9009 | 39200 | 0.0061 | - |
0.9021 | 39250 | 0.0508 | - |
0.9032 | 39300 | 0.214 | - |
0.9043 | 39350 | 0.0032 | - |
0.9055 | 39400 | 0.0234 | - |
0.9066 | 39450 | 0.0318 | - |
0.9078 | 39500 | 0.003 | - |
0.9089 | 39550 | 0.3719 | - |
0.9101 | 39600 | 0.0092 | - |
0.9112 | 39650 | 0.0027 | - |
0.9124 | 39700 | 0.3007 | - |
0.9135 | 39750 | 0.0535 | - |
0.9147 | 39800 | 0.0027 | - |
0.9158 | 39850 | 0.8316 | - |
0.9170 | 39900 | 0.3543 | - |
0.9181 | 39950 | 0.7228 | - |
0.9193 | 40000 | 0.4475 | - |
0.9204 | 40050 | 0.0044 | - |
0.9216 | 40100 | 0.0077 | - |
0.9227 | 40150 | 0.0668 | - |
0.9239 | 40200 | 0.0036 | - |
0.9250 | 40250 | 0.0032 | - |
0.9262 | 40300 | 0.035 | - |
0.9273 | 40350 | 0.011 | - |
0.9285 | 40400 | 0.0 | - |
0.9296 | 40450 | 0.5078 | - |
0.9308 | 40500 | 0.0003 | - |
0.9319 | 40550 | 0.0 | - |
0.9331 | 40600 | 0.0 | - |
0.9342 | 40650 | 0.0029 | - |
0.9354 | 40700 | 0.0001 | - |
0.9365 | 40750 | 0.0003 | - |
0.9377 | 40800 | 0.2938 | - |
0.9388 | 40850 | 0.0059 | - |
0.9400 | 40900 | 0.0646 | - |
0.9411 | 40950 | 0.0067 | - |
0.9423 | 41000 | 0.001 | - |
0.9434 | 41050 | 0.7928 | - |
0.9446 | 41100 | 0.0013 | - |
0.9457 | 41150 | 0.0271 | - |
0.9469 | 41200 | 0.0322 | - |
0.9480 | 41250 | 0.0127 | - |
0.9492 | 41300 | 0.0 | - |
0.9503 | 41350 | 0.4948 | - |
0.9515 | 41400 | 0.0185 | - |
0.9526 | 41450 | 0.4775 | - |
0.9538 | 41500 | 0.0046 | - |
0.9549 | 41550 | 0.0002 | - |
0.9561 | 41600 | 0.352 | - |
0.9572 | 41650 | 0.5607 | - |
0.9584 | 41700 | 0.0003 | - |
0.9595 | 41750 | 0.1911 | - |
0.9607 | 41800 | 0.0117 | - |
0.9618 | 41850 | 0.0008 | - |
0.9630 | 41900 | 0.0029 | - |
0.9641 | 41950 | 0.0034 | - |
0.9653 | 42000 | 0.0128 | - |
0.9664 | 42050 | 0.3599 | - |
0.9675 | 42100 | 0.5342 | - |
0.9687 | 42150 | 0.0333 | - |
0.9698 | 42200 | 0.0358 | - |
0.9710 | 42250 | 0.0039 | - |
0.9721 | 42300 | 0.0001 | - |
0.9733 | 42350 | 0.0066 | - |
0.9744 | 42400 | 0.0006 | - |
0.9756 | 42450 | 0.0005 | - |
0.9767 | 42500 | 0.5468 | - |
0.9779 | 42550 | 0.0121 | - |
0.9790 | 42600 | 0.0833 | - |
0.9802 | 42650 | 0.0152 | - |
0.9813 | 42700 | 0.001 | - |
0.9825 | 42750 | 0.0074 | - |
0.9836 | 42800 | 0.8221 | - |
0.9848 | 42850 | 0.0039 | - |
0.9859 | 42900 | 0.1647 | - |
0.9871 | 42950 | 0.0014 | - |
0.9882 | 43000 | 0.0006 | - |
0.9894 | 43050 | 0.0008 | - |
0.9905 | 43100 | 0.0 | - |
0.9917 | 43150 | 0.1409 | - |
0.9928 | 43200 | 0.0004 | - |
0.9940 | 43250 | 0.0006 | - |
0.9951 | 43300 | 0.0634 | - |
0.9963 | 43350 | 0.1843 | - |
0.9974 | 43400 | 0.0133 | - |
0.9986 | 43450 | 0.2553 | - |
0.9997 | 43500 | 0.0005 | - |
Framework Versions
- Python: 3.10.12
- SetFit: 1.0.3
- Sentence Transformers: 2.5.1
- Transformers: 4.38.2
- PyTorch: 2.1.0+cu121
- Datasets: 2.18.0
- Tokenizers: 0.15.2
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}
}