SentenceTransformer based on seongil-dn/unsupervised_20m_3800

This is a sentence-transformers model finetuned from seongil-dn/unsupervised_20m_3800. It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.

Model Details

Model Description

  • Model Type: Sentence Transformer
  • Base model: seongil-dn/unsupervised_20m_3800
  • Maximum Sequence Length: 1024 tokens
  • Output Dimensionality: 1024 dimensions
  • Similarity Function: Cosine Similarity

Model Sources

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 1024, 'do_lower_case': False}) with Transformer model: XLMRobertaModel 
  (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
  (2): Normalize()
)

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("seongil-dn/bge-m3-420")
# Run inference
sentences = [
    'Peter Stuyvesant, born in Holland, became Governor of which American city in 1647?',
    'Peter Stuyvesant (cigarette) half of its regular users"" and called the packaging changes ""the ultimate sick joke from big tobacco"". In 2013, it was reported that Imperial Tobacco Australia had sent marketing material to WA tobacco retailers which promotes limited edition packs of "Peter Stuyvesant + Loosie", which came with 26 cigarettes. The material included images of a young woman with pink hair putting on lipstick and men on the streets of New York and also included a calendar and small poster that were clearly intended to glamorise smoking. Anti-smoking campaigner Mike Daube said although the material did not break the law because',
    'Peter Stuyvesant (cigarette) can amount to millions of dollars and finally criminal prosecution - if companies wilfully break the laws. However last year, when questioned on why no such action was being pursued against Imperial Tobacco a spokeswoman for Federal Health said: ""No instances of non-compliance with the Act have been identified by the Department that warrant the initiation of Court proceedings in the first instance, and without attempting alternative dispute resolution to achieve compliance"". Peter Stuyvesant is or was sold in the following countries: Canada, United States, United Kingdom, Luxembourg, Belgium, The Netherlands, Germany, France, Austria, Switzerland, Spain, Italy, Czech Republic, Greece,',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 1024]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]

Training Details

Training Dataset

Unnamed Dataset

  • Size: 1,138,596 training samples
  • Columns: anchor, positive, negative, negative_2, negative_3, negative_4, and negative_5
  • Approximate statistics based on the first 1000 samples:
    anchor positive negative negative_2 negative_3 negative_4 negative_5
    type string string string string string string string
    details
    • min: 9 tokens
    • mean: 22.32 tokens
    • max: 119 tokens
    • min: 127 tokens
    • mean: 157.45 tokens
    • max: 420 tokens
    • min: 122 tokens
    • mean: 154.65 tokens
    • max: 212 tokens
    • min: 122 tokens
    • mean: 155.52 tokens
    • max: 218 tokens
    • min: 122 tokens
    • mean: 156.04 tokens
    • max: 284 tokens
    • min: 124 tokens
    • mean: 156.3 tokens
    • max: 268 tokens
    • min: 121 tokens
    • mean: 156.15 tokens
    • max: 249 tokens
  • Samples:
    anchor positive negative negative_2 negative_3 negative_4 negative_5
    What African country is projected to pass the United States in population by the year 2055? African immigration to the United States officially 40,000 African immigrants, although it has been estimated that the population is actually four times this number when considering undocumented immigrants. The majority of these immigrants were born in Ethiopia, Egypt, Nigeria, and South Africa. African immigrants like many other immigrant groups are likely to establish and find success in small businesses. Many Africans that have seen the social and economic stability that comes from ethnic enclaves such as Chinatowns have recently been establishing ethnic enclaves of their own at much higher rates to reap the benefits of such communities. Such examples include Little Ethiopia in Los Angeles and What Will Happen to the Gang Next Year? watching television at the time of the broadcast. This made it the lowest-rated episode in "30 Rock"'s history. and a decrease from the previous episode "The Return of Avery Jessup" (2.92 million) What Will Happen to the Gang Next Year? "What Will Happen to the Gang Next Year?" is the twenty-second and final episode of the sixth season of the American television comedy series "30 Rock", and the 125th overall episode of the series. It was directed by Michael Engler, and written by Matt Hubbard. The episode originally aired on the National Broadcasting Company (NBC) network in the United States Christianity in the United States Christ is the fifth-largest denomination, the largest Pentecostal church, and the largest traditionally African-American denomination in the nation. Among Eastern Christian denominations, there are several Eastern Orthodox and Oriental Orthodox churches, with just below 1 million adherents in the US, or 0.4% of the total population. Christianity was introduced to the Americas as it was first colonized by Europeans beginning in the 16th and 17th centuries. Going forward from its foundation, the United States has been called a Protestant nation by a variety of sources. Immigration further increased Christian numbers. Today most Christian churches in the United States are either What Will Happen to the Gang Next Year? What Will Happen to the Gang Next Year? "What Will Happen to the Gang Next Year?" is the twenty-second and final episode of the sixth season of the American television comedy series "30 Rock", and the 125th overall episode of the series. It was directed by Michael Engler, and written by Matt Hubbard. The episode originally aired on the National Broadcasting Company (NBC) network in the United States on May 17, 2012. In the episode, Jack (Alec Baldwin) and Avery (Elizabeth Banks) seek to renew their vows; Criss (James Marsden) sets out to show Liz (Tina Fey) he can pay History of the Jews in the United States Representatives by Rep. Samuel Dickstein (D; New York). This also failed to pass. During the Holocaust, fewer than 30,000 Jews a year reached the United States, and some were turned away due to immigration policies. The U.S. did not change its immigration policies until 1948. Currently, laws requiring teaching of the Holocaust are on the books in five states. The Holocaust had a profound impact on the community in the United States, especially after 1960, as Jews tried to comprehend what had happened, and especially to commemorate and grapple with it when looking to the future. Abraham Joshua Heschel summarized Public holidays in the United States will have very few customers that day. The labor force in the United States comprises about 62% (as of 2014) of the general population. In the United States, 97% of the private sector businesses determine what days this sector of the population gets paid time off, according to a study by the Society for Human Resource Management. The following holidays are observed by the majority of US businesses with paid time off: This list of holidays is based off the official list of federal holidays by year from the US Government. The holidays however are at the discretion of employers
    Which is the largest species of the turtle family? Loggerhead sea turtle turtle is debated, but most authors consider it a single polymorphic species. Molecular genetics has confirmed hybridization of the loggerhead sea turtle with the Kemp's ridley sea turtle, hawksbill sea turtle, and green sea turtles. The extent of natural hybridization is not yet determined; however, second-generation hybrids have been reported, suggesting some hybrids are fertile. Although evidence is lacking, modern sea turtles probably descended from a single common ancestor during the Cretaceous period. Like all other sea turtles except the leatherback, loggerheads are members of the ancient family Cheloniidae, and appeared about 40 million years ago. Of the six species Convention on the Conservation of Migratory Species of Wild Animals take joint action. At May 2018, there were 126 Parties to the Convention. The CMS Family covers a great diversity of migratory species. The Appendices of CMS include many mammals, including land mammals, marine mammals and bats; birds; fish; reptiles and one insect. Among the instruments, AEWA covers 254 species of birds that are ecologically dependent on wetlands for at least part of their annual cycle. EUROBATS covers 52 species of bat, the Memorandum of Understanding on the Conservation of Migratory Sharks seven species of shark, the IOSEA Marine Turtle MOU six species of marine turtle and the Raptors MoU Razor-backed musk turtle Razor-backed musk turtle The razor-backed musk turtle ("Sternotherus carinatus") is a species of turtle in the family Kinosternidae. The species is native to the southern United States. There are no subspecies that are recognized as being valid. "S. carinatus" is found in the states of Alabama, Arkansas, Louisiana, Mississippi, Oklahoma, and Texas. The razor-backed musk turtle grows to a straight carapace length of about . It has a brown-colored carapace, with black markings at the edges of each scute. The carapace has a distinct, sharp keel down the center of its length, giving the species its common name. The body African helmeted turtle African helmeted turtle The African helmeted turtle ("Pelomedusa subrufa"), also known commonly as the marsh terrapin, the crocodile turtle, or in the pet trade as the African side-necked turtle, is a species of omnivorous side-necked terrapin in the family Pelomedusidae. The species naturally occurs in fresh and stagnant water bodies throughout much of Sub-Saharan Africa, and in southern Yemen. The marsh terrapin is typically a rather small turtle, with most individuals being less than in straight carapace length, but one has been recorded with a length of . It has a black or brown carapace. The top of the tail Box turtle Box turtle Box turtles are North American turtles of the genus Terrapene. Although box turtles are superficially similar to tortoises in terrestrial habits and overall appearance, they are actually members of the American pond turtle family (Emydidae). The twelve taxa which are distinguished in the genus are distributed over four species. They are largely characterized by having a domed shell, which is hinged at the bottom, allowing the animal to close its shell tightly to escape predators. The genus name "Terrapene" was coined by Merrem in 1820 as a genus separate from "Emys" for those species which had a sternum Vallarta mud turtle Vallarta mud turtle The Vallarta mud turtle ("Kinosternon vogti") is a recently identified species of mud turtle in the family Kinosternidae. While formerly considered conspecific with the Jalisco mud turtle, further studies indicated that it was a separate species. It can be identified by a combination of the number of plastron and carapace scutes, body size, and the distinctive yellow rostral shield in males. It is endemic to Mexican state of Jalisco. It is only known from a few human-created or human-affected habitats (such as small streams and ponds) found around Puerto Vallarta. It is one of only 3 species
    How many gallons of beer are in an English barrel? Low-alcohol beer Prohibition in the United States. Near beer could not legally be labeled as "beer" and was officially classified as a "cereal beverage". The public, however, almost universally called it "near beer". The most popular "near beer" was Bevo, brewed by the Anheuser-Busch company. The Pabst company brewed "Pablo", Miller brewed "Vivo", and Schlitz brewed "Famo". Many local and regional breweries stayed in business by marketing their own near-beers. By 1921 production of near beer had reached over 300 million US gallons (1 billion L) a year (36 L/s). A popular illegal practice was to add alcohol to near beer. The Keg terms "half-barrel" and "quarter-barrel" are derived from the U.S. beer barrel, legally defined as being equal to 31 U.S. gallons (this is not the same volume as some other units also known as "barrels"). A 15.5 U.S. gallon keg is also equal to: However, beer kegs can come in many sizes: In European countries the most common keg size is 50 liters. This includes the UK, which uses a non-metric standard keg of 11 imperial gallons, which is coincidentally equal to . The German DIN 6647-1 and DIN 6647-2 have also defined kegs in the sizes of 30 and 20 Beer in Chile craft beers. They are generally low or very low volume producers. In Chile there are more than 150 craft beer producers distributed along the 15 Chilean Regions. The list below includes: Beer in Chile The primary beer brewed and consumed in Chile is pale lager, though the country also has a tradition of brewing corn beer, known as chicha. Chile’s beer history has a strong German influence – some of the bigger beer producers are from the country’s southern lake district, a region populated by a great number of German immigrants during the 19th century. Chile also produces English ale-style Barrel variation. In modern times, produce barrels for all dry goods, excepting cranberries, contain 7,056 cubic inches, about 115.627 L. Barrel A barrel, cask, or tun is a hollow cylindrical container, traditionally made of wooden staves bound by wooden or metal hoops. Traditionally, the barrel was a standard size of measure referring to a set capacity or weight of a given commodity. For example, in the UK a barrel of beer refers to a quantity of . Wine was shipped in barrels of . Modern wooden barrels for wine-making are either made of French common oak ("Quercus robur") and white oak The Rare Barrel The Rare Barrel The Rare Barrel is a brewery and brewpub in Berkeley, California, United States, that exclusively produces sour beers. Founders Jay Goodwin and Alex Wallash met while attending UCSB. They started home-brewing in their apartment and decided that they would one day start a brewery together. Goodwin started working at The Bruery, where he worked his way from a production assistant to brewer, eventually becoming the head of their barrel aging program. The Rare Barrel brewed its first batch of beer in February 2013, and opened its tasting room on December 27, 2013. The Rare Barrel was named Barrel (unit) Barrel (unit) A barrel is one of several units of volume applied in various contexts; there are dry barrels, fluid barrels (such as the UK beer barrel and US beer barrel), oil barrels and so on. For historical reasons the volumes of some barrel units are roughly double the volumes of others; volumes in common usage range from about . In many connections the term "drum" is used almost interchangeably with "barrel". Since medieval times the term barrel as a unit of measure has had various meanings throughout Europe, ranging from about 100 litres to 1000 litres. The name was
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'guide': SentenceTransformer(
      (0): Transformer({'max_seq_length': 1024, 'do_lower_case': False}) with Transformer model: XLMRobertaModel 
      (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
      (2): Normalize()
    ), 'temperature': 0.01}
    

Training Hyperparameters

Non-Default Hyperparameters

  • per_device_train_batch_size: 1024
  • learning_rate: 3e-05
  • weight_decay: 0.01
  • warmup_ratio: 0.05
  • bf16: True
  • batch_sampler: no_duplicates

All Hyperparameters

Click to expand
  • overwrite_output_dir: False
  • do_predict: False
  • eval_strategy: no
  • prediction_loss_only: True
  • per_device_train_batch_size: 1024
  • per_device_eval_batch_size: 8
  • per_gpu_train_batch_size: None
  • per_gpu_eval_batch_size: None
  • gradient_accumulation_steps: 1
  • eval_accumulation_steps: None
  • torch_empty_cache_steps: None
  • learning_rate: 3e-05
  • weight_decay: 0.01
  • adam_beta1: 0.9
  • adam_beta2: 0.999
  • adam_epsilon: 1e-08
  • max_grad_norm: 1.0
  • num_train_epochs: 3
  • max_steps: -1
  • lr_scheduler_type: linear
  • lr_scheduler_kwargs: {}
  • warmup_ratio: 0.05
  • warmup_steps: 0
  • log_level: passive
  • log_level_replica: warning
  • log_on_each_node: True
  • logging_nan_inf_filter: True
  • save_safetensors: True
  • save_on_each_node: False
  • save_only_model: False
  • restore_callback_states_from_checkpoint: False
  • no_cuda: False
  • use_cpu: False
  • use_mps_device: False
  • seed: 42
  • data_seed: None
  • jit_mode_eval: False
  • use_ipex: False
  • bf16: True
  • fp16: False
  • fp16_opt_level: O1
  • half_precision_backend: auto
  • bf16_full_eval: False
  • fp16_full_eval: False
  • tf32: None
  • local_rank: 0
  • ddp_backend: None
  • tpu_num_cores: None
  • tpu_metrics_debug: False
  • debug: []
  • dataloader_drop_last: True
  • dataloader_num_workers: 0
  • dataloader_prefetch_factor: None
  • past_index: -1
  • disable_tqdm: False
  • remove_unused_columns: True
  • label_names: None
  • load_best_model_at_end: False
  • ignore_data_skip: False
  • fsdp: []
  • fsdp_min_num_params: 0
  • fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
  • fsdp_transformer_layer_cls_to_wrap: None
  • accelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
  • deepspeed: None
  • label_smoothing_factor: 0.0
  • optim: adamw_torch
  • optim_args: None
  • adafactor: False
  • group_by_length: False
  • length_column_name: length
  • ddp_find_unused_parameters: None
  • ddp_bucket_cap_mb: None
  • ddp_broadcast_buffers: False
  • dataloader_pin_memory: True
  • dataloader_persistent_workers: False
  • skip_memory_metrics: True
  • use_legacy_prediction_loop: False
  • push_to_hub: False
  • resume_from_checkpoint: None
  • hub_model_id: None
  • hub_strategy: every_save
  • hub_private_repo: None
  • hub_always_push: False
  • gradient_checkpointing: False
  • gradient_checkpointing_kwargs: None
  • include_inputs_for_metrics: False
  • include_for_metrics: []
  • eval_do_concat_batches: True
  • fp16_backend: auto
  • push_to_hub_model_id: None
  • push_to_hub_organization: None
  • mp_parameters:
  • auto_find_batch_size: False
  • full_determinism: False
  • torchdynamo: None
  • ray_scope: last
  • ddp_timeout: 1800
  • torch_compile: False
  • torch_compile_backend: None
  • torch_compile_mode: None
  • dispatch_batches: None
  • split_batches: None
  • include_tokens_per_second: False
  • include_num_input_tokens_seen: False
  • neftune_noise_alpha: None
  • optim_target_modules: None
  • batch_eval_metrics: False
  • eval_on_start: False
  • use_liger_kernel: False
  • eval_use_gather_object: False
  • average_tokens_across_devices: False
  • prompts: None
  • batch_sampler: no_duplicates
  • multi_dataset_batch_sampler: proportional

Training Logs

Click to expand
Epoch Step Training Loss
0.0036 1 1.0283
0.0072 2 1.0155
0.0108 3 0.9858
0.0144 4 0.9519
0.0181 5 0.9434
0.0217 6 0.898
0.0253 7 0.8798
0.0289 8 0.7976
0.0325 9 0.7797
0.0361 10 0.7464
0.0397 11 0.743
0.0433 12 0.716
0.0469 13 0.7076
0.0505 14 0.666
0.0542 15 0.631
0.0578 16 0.5905
0.0614 17 0.6537
0.0650 18 0.5755
0.0686 19 0.5422
0.0722 20 0.5393
0.0758 21 0.5741
0.0794 22 0.498
0.0830 23 0.5522
0.0866 24 0.5592
0.0903 25 0.4797
0.0939 26 0.4684
0.0975 27 0.5207
0.1011 28 0.4692
0.1047 29 0.4459
0.1083 30 0.4439
0.1119 31 0.4656
0.1155 32 0.4737
0.1191 33 0.4391
0.1227 34 0.4386
0.1264 35 0.4107
0.1300 36 0.4513
0.1336 37 0.3789
0.1372 38 0.4103
0.1408 39 0.3929
0.1444 40 0.4226
0.1480 41 0.391
0.1516 42 0.3674
0.1552 43 0.3607
0.1588 44 0.3738
0.1625 45 0.3842
0.1661 46 0.3498
0.1697 47 0.3586
0.1733 48 0.3538
0.1769 49 0.3572
0.1805 50 0.3547
0.1841 51 0.3179
0.1877 52 0.3436
0.1913 53 0.3502
0.1949 54 0.3381
0.1986 55 0.3547
0.2022 56 0.3362
0.2058 57 0.3407
0.2094 58 0.31
0.2130 59 0.3039
0.2166 60 0.3362
0.2202 61 0.2948
0.2238 62 0.3429
0.2274 63 0.3096
0.2310 64 0.35
0.2347 65 0.2997
0.2383 66 0.3258
0.2419 67 0.3376
0.2455 68 0.3213
0.2491 69 0.3185
0.2527 70 0.3282
0.2563 71 0.2988
0.2599 72 0.33
0.2635 73 0.3066
0.2671 74 0.3303
0.2708 75 0.3067
0.2744 76 0.2996
0.2780 77 0.3063
0.2816 78 0.3235
0.2852 79 0.2902
0.2888 80 0.302
0.2924 81 0.3223
0.2960 82 0.297
0.2996 83 0.2936
0.3032 84 0.3279
0.3069 85 0.2973
0.3105 86 0.2881
0.3141 87 0.3014
0.3177 88 0.2986
0.3213 89 0.3057
0.3249 90 0.2887
0.3285 91 0.2765
0.3321 92 0.2818
0.3357 93 0.2904
0.3394 94 0.267
0.3430 95 0.2948
0.3466 96 0.2766
0.3502 97 0.2782
0.3538 98 0.3082
0.3574 99 0.2697
0.3610 100 0.3006
0.3646 101 0.2986
0.3682 102 0.2789
0.3718 103 0.2756
0.3755 104 0.2884
0.3791 105 0.273
0.3827 106 0.2687
0.3863 107 0.2808
0.3899 108 0.2763
0.3935 109 0.2738
0.3971 110 0.2642
0.4007 111 0.2612
0.4043 112 0.2859
0.4079 113 0.2558
0.4116 114 0.2565
0.4152 115 0.2747
0.4188 116 0.2684
0.4224 117 0.2643
0.4260 118 0.241
0.4296 119 0.2563
0.4332 120 0.2754
0.4368 121 0.2503
0.4404 122 0.2544
0.4440 123 0.2729
0.4477 124 0.2589
0.4513 125 0.2626
0.4549 126 0.2693
0.4585 127 0.2687
0.4621 128 0.2903
0.4657 129 0.2663
0.4693 130 0.2604
0.4729 131 0.2601
0.4765 132 0.2649
0.4801 133 0.2597
0.4838 134 0.2608
0.4874 135 0.245
0.4910 136 0.2587
0.4946 137 0.2618
0.4982 138 0.2599
0.5018 139 0.265
0.5054 140 0.2427
0.5090 141 0.2448
0.5126 142 0.2608
0.5162 143 0.2188
0.5199 144 0.2471
0.5235 145 0.2604
0.5271 146 0.2571
0.5307 147 0.2684
0.5343 148 0.2319
0.5379 149 0.2572
0.5415 150 0.2243
0.5451 151 0.2562
0.5487 152 0.2457
0.5523 153 0.255
0.5560 154 0.2664
0.5596 155 0.24
0.5632 156 0.2612
0.5668 157 0.243
0.5704 158 0.2345
0.5740 159 0.2359
0.5776 160 0.2384
0.5812 161 0.2541
0.5848 162 0.2496
0.5884 163 0.2429
0.5921 164 0.2411
0.5957 165 0.2261
0.5993 166 0.2164
0.6029 167 0.2251
0.6065 168 0.2417
0.6101 169 0.2494
0.6137 170 0.2359
0.6173 171 0.2489
0.6209 172 0.2261
0.6245 173 0.2367
0.6282 174 0.2355
0.6318 175 0.2423
0.6354 176 0.2454
0.6390 177 0.2438
0.6426 178 0.2415
0.6462 179 0.2237
0.6498 180 0.2419
0.6534 181 0.2373
0.6570 182 0.2659
0.6606 183 0.2201
0.6643 184 0.2342
0.6679 185 0.2149
0.6715 186 0.2241
0.6751 187 0.2443
0.6787 188 0.2489
0.6823 189 0.2354
0.6859 190 0.2483
0.6895 191 0.2193
0.6931 192 0.229
0.6968 193 0.2335
0.7004 194 0.2484
0.7040 195 0.2317
0.7076 196 0.2203
0.7112 197 0.2329
0.7148 198 0.2084
0.7184 199 0.2341
0.7220 200 0.2369
0.7256 201 0.2364
0.7292 202 0.2276
0.7329 203 0.215
0.7365 204 0.2486
0.7401 205 0.2237
0.7437 206 0.218
0.7473 207 0.2444
0.7509 208 0.2276
0.7545 209 0.2127
0.7581 210 0.2283
0.7617 211 0.2234
0.7653 212 0.207
0.7690 213 0.24
0.7726 214 0.2317
0.7762 215 0.2056
0.7798 216 0.2149
0.7834 217 0.2211
0.7870 218 0.2232
0.7906 219 0.2222
0.7942 220 0.2481
0.7978 221 0.227
0.8014 222 0.2305
0.8051 223 0.2091
0.8087 224 0.2278
0.8123 225 0.2123
0.8159 226 0.2233
0.8195 227 0.2365
0.8231 228 0.2165
0.8267 229 0.2192
0.8303 230 0.2145
0.8339 231 0.2382
0.8375 232 0.2232
0.8412 233 0.2273
0.8448 234 0.2296
0.8484 235 0.2229
0.8520 236 0.2213
0.8556 237 0.2343
0.8592 238 0.2208
0.8628 239 0.2315
0.8664 240 0.2137
0.8700 241 0.2201
0.8736 242 0.2185
0.8773 243 0.2337
0.8809 244 0.2153
0.8845 245 0.2369
0.8881 246 0.2216
0.8917 247 0.2338
0.8953 248 0.2241
0.8989 249 0.213
0.9025 250 0.2245
0.9061 251 0.2074
0.9097 252 0.2283
0.9134 253 0.2003
0.9170 254 0.2099
0.9206 255 0.2288
0.9242 256 0.2168
0.9278 257 0.215
0.9314 258 0.2146
0.9350 259 0.2126
0.9386 260 0.2178
0.9422 261 0.2065
0.9458 262 0.2327
0.9495 263 0.2116
0.9531 264 0.2324
0.9567 265 0.2235
0.9603 266 0.2189
0.9639 267 0.2175
0.9675 268 0.2171
0.9711 269 0.1925
0.9747 270 0.225
0.9783 271 0.2149
0.9819 272 0.204
0.9856 273 0.2004
0.9892 274 0.2055
0.9928 275 0.2045
0.9964 276 0.2186
1.0 277 0.2215
1.0036 278 0.1545
1.0072 279 0.169
1.0108 280 0.152
1.0144 281 0.1597
1.0181 282 0.1626
1.0217 283 0.1692
1.0253 284 0.1639
1.0289 285 0.1638
1.0325 286 0.1507
1.0361 287 0.1594
1.0397 288 0.1621
1.0433 289 0.1565
1.0469 290 0.1549
1.0505 291 0.1731
1.0542 292 0.152
1.0578 293 0.1586
1.0614 294 0.1593
1.0650 295 0.1406
1.0686 296 0.1524
1.0722 297 0.1474
1.0758 298 0.158
1.0794 299 0.1743
1.0830 300 0.1485
1.0866 301 0.1648
1.0903 302 0.1337
1.0939 303 0.1554
1.0975 304 0.1434
1.1011 305 0.1642
1.1047 306 0.159
1.1083 307 0.1658
1.1119 308 0.1554
1.1155 309 0.1425
1.1191 310 0.1432
1.1227 311 0.1517
1.1264 312 0.148
1.1300 313 0.1636
1.1336 314 0.1735
1.1372 315 0.151
1.1408 316 0.1423
1.1444 317 0.1501
1.1480 318 0.1537
1.1516 319 0.1554
1.1552 320 0.1553
1.1588 321 0.149
1.1625 322 0.1605
1.1661 323 0.1551
1.1697 324 0.1555
1.1733 325 0.1443
1.1769 326 0.1533
1.1805 327 0.1658
1.1841 328 0.15
1.1877 329 0.1626
1.1913 330 0.172
1.1949 331 0.1542
1.1986 332 0.166
1.2022 333 0.1513
1.2058 334 0.1612
1.2094 335 0.1521
1.2130 336 0.1552
1.2166 337 0.1503
1.2202 338 0.1613
1.2238 339 0.1563
1.2274 340 0.1429
1.2310 341 0.1587
1.2347 342 0.1477
1.2383 343 0.1561
1.2419 344 0.1418
1.2455 345 0.1495
1.2491 346 0.1533
1.2527 347 0.1521
1.2563 348 0.1422
1.2599 349 0.1446
1.2635 350 0.146
1.2671 351 0.1473
1.2708 352 0.1566
1.2744 353 0.1411
1.2780 354 0.1502
1.2816 355 0.1383
1.2852 356 0.1622
1.2888 357 0.1391
1.2924 358 0.1455
1.2960 359 0.1541
1.2996 360 0.1476
1.3032 361 0.1662
1.3069 362 0.1476
1.3105 363 0.1452
1.3141 364 0.1372
1.3177 365 0.1542
1.3213 366 0.1531
1.3249 367 0.1623
1.3285 368 0.1544
1.3321 369 0.1625
1.3357 370 0.1459
1.3394 371 0.1474
1.3430 372 0.1499
1.3466 373 0.1495
1.3502 374 0.1361
1.3538 375 0.1444
1.3574 376 0.1495
1.3610 377 0.1583
1.3646 378 0.1642
1.3682 379 0.1646
1.3718 380 0.1595
1.3755 381 0.149
1.3791 382 0.1448
1.3827 383 0.1603
1.3863 384 0.1269
1.3899 385 0.1491
1.3935 386 0.1367
1.3971 387 0.1501
1.4007 388 0.1414
1.4043 389 0.156
1.4079 390 0.1428
1.4116 391 0.1559
1.4152 392 0.1452
1.4188 393 0.1547
1.4224 394 0.1432
1.4260 395 0.1648
1.4296 396 0.166
1.4332 397 0.1485
1.4368 398 0.1494
1.4404 399 0.1635
1.4440 400 0.1498
1.4477 401 0.1509
1.4513 402 0.1431
1.4549 403 0.1547
1.4585 404 0.1576
1.4621 405 0.1426
1.4657 406 0.132
1.4693 407 0.1511
1.4729 408 0.1551
1.4765 409 0.16
1.4801 410 0.1507
1.4838 411 0.1591
1.4874 412 0.1536
1.4910 413 0.1507
1.4946 414 0.1564
1.4982 415 0.153
1.5018 416 0.1404
1.5054 417 0.1627
1.5090 418 0.1432
1.5126 419 0.1456
1.5162 420 0.1369

Framework Versions

  • Python: 3.10.12
  • Sentence Transformers: 3.4.1
  • Transformers: 4.49.0
  • PyTorch: 2.5.1+cu124
  • Accelerate: 1.4.0
  • Datasets: 3.3.2
  • Tokenizers: 0.21.0

Citation

BibTeX

Sentence Transformers

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}
Downloads last month
6
Safetensors
Model size
568M params
Tensor type
F32
·
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.

Model tree for seongil-dn/bge-m3-420

Finetuned
(6)
this model