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SentenceTransformer based on BAAI/bge-base-en-v1.5

This is a sentence-transformers model finetuned from BAAI/bge-base-en-v1.5. It maps sentences & paragraphs to a 768-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: BAAI/bge-base-en-v1.5
  • Maximum Sequence Length: 512 tokens
  • Output Dimensionality: 768 tokens
  • Similarity Function: Cosine Similarity

Model Sources

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': True}) with Transformer model: BertModel 
  (1): Pooling({'word_embedding_dimension': 768, '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("phamkinhquoc2002/bge-base-financial-matryoshka_test")
# Run inference
sentences = [
    "Start with a billion, and invest it poorly. \n\nSeriously though, just invest as much as you can into total market index funds. Start with tax advantaged accounts, and work your way up from there. I started investing about 8 years ago, when my wife and I made a combine maybe $60k a year. We've worked our way up to to around $150k a year. Current net worth is around $400k and growing. Compound interest is the most powerful force on earth.",
    'Hey is anyone in here a millionaire or ever made a million dollars? What’s your advice on how to make a million dollars? Obviously I could just save my money for a long time and have a million in like 25 years or longer but what’s advice on how to make a million dollars in like 10 years? I’m 25 years old and am 6 months in to electrician apprentice',
    "The new car is on avg. $40,000, and the homes people buy are usually way above their pay grade. I see people making minimum wage buying a PS5 and fast food and unlimited data, etc. I make alright money and am frugal, no debt, and still I'm struggling to plan for kids, a home, and retirement. Is everyone just in massive debt? Is this sustainable or will it cause another crash?",
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]

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

Evaluation

Metrics

Information Retrieval

Metric Value
cosine_accuracy@1 0.38
cosine_accuracy@3 0.63
cosine_accuracy@5 0.71
cosine_accuracy@10 0.74
cosine_precision@1 0.38
cosine_precision@3 0.21
cosine_precision@5 0.142
cosine_precision@10 0.074
cosine_recall@1 0.38
cosine_recall@3 0.63
cosine_recall@5 0.71
cosine_recall@10 0.74
cosine_ndcg@10 0.5691
cosine_mrr@10 0.5131
cosine_map@100 0.5249

Information Retrieval

Metric Value
cosine_accuracy@1 0.4
cosine_accuracy@3 0.6
cosine_accuracy@5 0.71
cosine_accuracy@10 0.76
cosine_precision@1 0.4
cosine_precision@3 0.2
cosine_precision@5 0.142
cosine_precision@10 0.076
cosine_recall@1 0.4
cosine_recall@3 0.6
cosine_recall@5 0.71
cosine_recall@10 0.76
cosine_ndcg@10 0.5801
cosine_mrr@10 0.5221
cosine_map@100 0.5322

Information Retrieval

Metric Value
cosine_accuracy@1 0.37
cosine_accuracy@3 0.58
cosine_accuracy@5 0.66
cosine_accuracy@10 0.76
cosine_precision@1 0.37
cosine_precision@3 0.1933
cosine_precision@5 0.132
cosine_precision@10 0.076
cosine_recall@1 0.37
cosine_recall@3 0.58
cosine_recall@5 0.66
cosine_recall@10 0.76
cosine_ndcg@10 0.5568
cosine_mrr@10 0.4927
cosine_map@100 0.5028

Information Retrieval

Metric Value
cosine_accuracy@1 0.38
cosine_accuracy@3 0.53
cosine_accuracy@5 0.65
cosine_accuracy@10 0.72
cosine_precision@1 0.38
cosine_precision@3 0.1767
cosine_precision@5 0.13
cosine_precision@10 0.072
cosine_recall@1 0.38
cosine_recall@3 0.53
cosine_recall@5 0.65
cosine_recall@10 0.72
cosine_ndcg@10 0.5382
cosine_mrr@10 0.4811
cosine_map@100 0.4942

Information Retrieval

Metric Value
cosine_accuracy@1 0.3
cosine_accuracy@3 0.47
cosine_accuracy@5 0.56
cosine_accuracy@10 0.66
cosine_precision@1 0.3
cosine_precision@3 0.1567
cosine_precision@5 0.112
cosine_precision@10 0.066
cosine_recall@1 0.3
cosine_recall@3 0.47
cosine_recall@5 0.56
cosine_recall@10 0.66
cosine_ndcg@10 0.4707
cosine_mrr@10 0.4112
cosine_map@100 0.4253

Training Details

Training Dataset

Unnamed Dataset

  • Size: 100 training samples
  • Columns: positive and anchor
  • Approximate statistics based on the first 1000 samples:
    positive anchor
    type string string
    details
    • min: 42 tokens
    • mean: 181.37 tokens
    • max: 512 tokens
    • min: 36 tokens
    • mean: 297.07 tokens
    • max: 512 tokens
  • Samples:
    positive anchor
    (relix already hit on some of this)

    It's hard to explain this to a five-year-old, because there are some fairly abstract concepts involved, but here goes...

    All actual "money" is debt. All of it, including monetary gold, etc. (Don't argue with me yet, I'll get to that.)

    Imagine a pretend world with no money, some kind of primitive villiage or something. Now let's invent paper money. You can't just print a bunch of paper that says people have to give you stuff, because nobody would honor it. But you *could* print IOUs. Let's walk through this...

    - Let's say you're an apple-farmer and I'm a hunter. You want some meat but haven't harvested your crops yet. You say to me, "hey, go hunt me some meat and I'll give you 1/10th of my apple harvest in the fall". Fair enough, I give you meat, you owe me apples. There's probably a lot of this kind of stuff going on, in addition to normal barter. In time, standard "prices" start to emerge: a deer haunch is worth a bushel of apples, or whatever.

    - Now, let's say a week later, I realize that my kid needs a new pair of shoes more than I need a bushel of apples. I come back to you and say, "Hey remember that bushel of apples you owe me? Could you write a marker, redeemable for one bushel of apples, that I can give to the shoemaker in trade for a pair of shoes?" You say okay, and we have invented a *transferable note*, something a lot like money.

    - In time, our little villiage starts to figure out that a note redeemable for a bushel of apples can be swapped for all kinds of things. The fisherman who doesn't even like apples will accept apple-certificates in trade for fish, because he knows he can trade them to boat-builder who loves apples. In time, you can even start to hire farm-workers without giving them anything except a note promising a cut of the future harvest.

    Now, you are issuing *debt*: a promise to provide apples. The "money" is a transferable IOU-- your workers get a promise to provide value equal to a day of farm-work, or whatever, and it's transferrable, so they can use it to buy whatever they want. The worker gets fish from the fisherman, not in exchange for doing any work or giving him anything he can use, but in exchange for an IOU that the fisherman can redeem anywhere.

    So far so good. But there are a couple of forks in the road here, on the way to a realistic monetary system, that we'll address separately:

    - What happens if your apple orchard is destroyed in a wildfire? Suddenly all the notes that everyone has been trading are basically wiped out. It didn't "go" anywhere, it's just gone, it doesn't exist. Real value was genuinely destroyed. There is no thermodynamic law of the conservation of monetary value-- just as you and I created it by creating transferable debt, it can also be genuinely destroyed. (We'll get back to this in a minute, it gets interesting).

    - The second issue is that, in all probability, the whole town is not *just* trading apple-certificates. I could also issue promises to catch deer, the fisherman could issue promises of fish, and so on. This could get pretty messy, especially if you got the notion to issue more apple-certificates than you can grow: you could buy all kinds of stuff with self-issued debt that you could never repay, and the town wouldn't find out until harvest-time comes. Once again, value has been "destroyed" people worked and made stuff and gave you stuff in exchange for something that doesn't exist, and will never exist. All that stuff they made is gone, you consumed it, and there is nothing to show for it.

    The above two concerns are likely to become manifest in our village sooner or later, and probably sooner. This leads to the question of *credit*, which is, at its most basic, a measure of *credibility*. Every time you issue an apple-certificate, you are *borrowing*, with a promise to repay from future apple-harvests.

    After the first couple of town scandals, people will start taking a closer look at the credibility of the issuer. Let's say the town potato-farmer comes up with a scheme where his potato-certificates are actually issued by some credible third-party, say the town priest or whatever, who starts every growing season with a book of numbered certificates equal to the typical crop-yield and no more, and keeps half of the certificate on file, issuing the other half. Now there is an audit trail and a very credible system that is likely to earn the potato-grower a lot of credit, compared to other farmers in town. That means that the potato-grower can probably issue more notes at a better exchange rate than some murkier system. Similarly, the town drunk probably won't get much value for his certificates promising a ship of gold.

    Now we have something like a credit market emerging, and the potato-farmer is issuing something closer to what we might call a modern "bond"...

    (continued in a reply to this post...)

    Honest question.

    Where is all the money? I hear nothing but bad news about financial crisis all over the world, and it seems that there is a shortage of cash - like it is some sort of natural resource.

    People haven't stopped buying stuff. They still need food, clothing, medicine, shelter. Taxes are still collected. Fines are still levied.

    So where is all the money? I mean, labor has been produced to make things and wages paid to the laborers. The things are purchased by other laborers, who were paid for producing goods or services, etc. It's a closed loop, right?

    Can someone explain it like I'm five or something?
    I someone were to make a good alternative then I'd be very happy about it. It can take ages moderating this sub. I'm sure lots of the other mods think the same.

    The fundamental problem is though that loads of people who don't know about economic write replies. All sorts of bullshit gets written. The problem then is you'd have to know about economics to distinguish the bullshit from the truth.

    If someone can think of a good way of solving this I'd be very happy.
    So often someone will ask an amazing question, something I’m really interested in getting a good answer to, or even someone’s opinion, but I always just see that message explaining that comments need to be approved.

    99.9% is an exaggeration, but not many people are going to come back to look at a post to see if any comments have been approved.
    So I said I would talk about the US Military if this got any interest. Here goes:

    The US Department of Defense (hereafter DOD) has put in place a ton of procedural protections to stave off corruption. And God knows they need protection: only in the DOD can you find a 20-something purchasing officer who knows nothing about the stuff he's buying, who makes around $30k per year, and who is in charge of a half-billion-dollar budget.

    For starters, low-paid people with large purchasing budgets are the easiest to corrupt outright. Find someone makes $30,000 per year but who has a $10m budget, and you have struck gold: it doesn't even require outright bribery.

    Just show up at their office and mention that you might have some product for them to take a look at... "Can you spare some time this weekend? I have tickets to the playoffs if you're free... Whoa!? You're a fisherman? Let's forget about business: why not have the family come by the beach house? I just got a new boat and the stripers are running... we'll talk business later..."

    Take a guy living in a military-base trailer out fishing on a yacht or to courtside seats, take him on a golf weekend, or to front-row seats at an A-list concert, hell, even just take him and his lady to a swank restaurant, and you've made a new best friend. And if he happens to be in charge of a $10m budget, that lavish night might be about to pay for itself 100,000 times over.

    And all that assumes that you did not actually have a stripper with a cell-phone camera waiting in the car after the concert... we haven't even talked about blackmail, so why bring it up? Especially considering that these days, you don't even have to blackmail someone to blackmail them-- just linking your pics to their facebook, or setting up a "my party with Joe Blow" web page can ruin their life without malice or legal consequence... We're just posting our own party pics!

    The DOD grades proposals with a color-grading system that is basically equivalent to letter grades.

    The way it works is: the purchasing officer or whomever writes the spec ("request for quote"-- in normal business this called a "request for proposal" or "RFP". The DOD calls it an "RFQ". Whatever.). The spec is written as numbered sentences/paragraphs. Companies write bids that answer each number, with a bottom-line price.

    A technical review committee sees the proposals with the price and supplier blacked out, and "grades" each proposal based on how well it meets the spec. The purchasing officer then sees the "grades" from the technical review, with the prices alongside (but not the complete proposals). Depending on his instructions, he may be required to either sign for the best overall value, highest overall grade, lowest acceptable cost, etc.

    All of this seems very official and corruption-proof, until you realize that the original request for proposal came from, say, a 65-year-old Naval Admiral who knows everything about Oceanic warfare but nothing at all about computers, who assigned his 20-something first mate to write the spec and request for funding, who knows nothing about purchasing and who in turn wrote a spec (two years ago) that required Core2duo computers with 2GB ram and Windows XP and who required computers that meet the spec...

    By the time Congress approves the funding, the spec is obsolete, and it costs far *more* to buy a bunch of obsolete Core2Duo machines with 2GB RAM than it would have cost to buy more-powerful computers at Costco.

    The over-technicality and protectiveness of the DOD actually makes it one of the most vulnerable purchasing systems anywhere. As a technical officer who was interested in my product told me: "Don't worry about the review process, we'll just let you guys write the spec". If the military wants a Mercedes, they just issue a spec that requires a hood ornament with three lines trisecting a circle, and see whichever car company meets the spec at the best price-- surprise! They get the contract. Which means that the DOD is probably the only buyer in the world paying sticker price.
    This is a throwaway account (I'm a longtime redditor under another login). /r/economics might not be the correct place to put this, but it was the best I could think of. I'm a mid-career guy in a business that does a lot of work with governmental and quasi-governmental agencies. I've never ripped anyone off personally, but I have seen and occasionally been an incidental beneficiary of quite a bit of patronage, insider dealing, nepotism, misuse of taxpayer money, and outright corruption. While I have always been honest in my own dealings on a case-by-case basis, I have refrained from many opportunities to be a "whistleblower".

    A lot of stuff on reddit misunderstands the relationships between wealth, power, and influence. For starters, all the above three are always and have always been inter-related, and probably always will be. And that might not always be a bad thing: those who have risen to high levels of wealth are often pretty smart, and surprisingly often exceptionally honest. Those who rise to high levels of influence usually have some pretty good insight and talent in their area of expertise. Those who have acquired a lot of power tend to be good at accomplishing things that lots of people want to see happen.

    None of which is purely democratic, nor even purely meritocratic, but there is a certain dose of both kind of baked into the cake: stuff like wealth or family connections only gets you so far in modern, developed, and relatively open and transparent societies such as the US. And while that can be pretty far by normal standards, at some point sunlight does shine through any crack, and outright robbery or complete incompetence is difficult to sustain indefinitely.

    But there is an awful lot of low-level waste, patronage, and corruption that happens both in the private and in the public sector.

    Without going ideological, the private sector in a free-ish market has a more immediate system of checks and balances if only because you have to actually persuade the end users to keep buying your stuff for the price you're charging: if it's no good, or if you are grossly over-charging, your customers will tend to catch on sooner or later.

    But in the public sector, the "consumer" often has little choice... so-called "market discipline" is a lot more diffuse when you have a former-schoolteacher-or-real-estate-broker-turned city councilman whose job it is to disburse a multi-million-dollar street-paving contract or whatever. And neither the schoolteacher nor the real-estate broker has any clue how to write or evaluate a road-paving contract...

    Let's say that there are three credible bidders for that street-paving contract:

    * Bidder 1 is "Paver Joe", a local guy with a driveway-paving company and three trucks who sees this as a big opportunity to expand his business and get the city to pay for five new trucks. He puts in a dirt-cheap bid that he wrote up himself with the help of his estate attorney. The cost to taxpayers is very low, but the certainty that he will complete it on schedule and as specified is a little iffy. Paver Joe plans to work overtime and bust his tail on the job, not for profits, but to grow his business. He's offering the taxpayers a great deal, but a slightly risky one.

    * Bidder 2 is "Muni Paver Inc", a company who has the experience and expertise to do the job, who knows what's involved and who has done this work before. They already have the trucks, their workers are all unionized and paid "prevailing wage", everything will be done by the book, all their EPA certifications are in place, etc... The bid is a lot more expensive than Paver Joe, but it's credible and reliable. They are offering the taxpayers a degree of certainty and confidence that Paver Joe cannot match.

    * Bidder 3 is me, "Corruptocorp". Instead of Paver Joe's 2-page contract with typos, or Muni-Paving's 20-page contract, I'm offering the city council a full package of videos, brochures, and a 40-page contract with a price just a tad higher than Paver Joe (my quoted price is meaningless, as we will see). Moreover, I'm inviting the city council to Corruptocorp-owned suites in a golf resort near my headquarters to give my presentation (all expenses paid, of course, and of course, bring your spouses). There the city council members will, after the first day of golf, dinner, dancing, and cocktails, see a slideshow and chorus-line of smiling multi-ethnic faces and working mothers talking about how much Corruptocorp's paving improved their town and their lives. I'll then stand up and tell a self-effacing joke about being one of those corporate guys trying to get their money, and then I'll wax a bit emotional about my small-town roots and how Corruptocorp was started by a man with a simple dream to make life better for everyone, and to do well by doing good in local communities, and that we actually plan to hire local contractors such as Joe's Paving to do the work, backed our economies of scale and reliability. I'll mention that paragraph 32 subsection B of our proposal mandates twice-yearly performance reviews by the city council, to of course be held at the golf resort, at Corruptocorp's expense, ("so I hope to see you all back here every February and August!"), and of course I make sure that each of them has my "personal" cell phone and home numbers in case they have any questions....

    So needless to say I get the bid, and six months later it's time for our review at the golf resort. After dinner and cocktails I step up to the podium and announce that there is both good news and bad news:

    *"The bad news is that our subcontractor has found over 1,000 rocks in the road. And as I'm sure you know, paragraph 339 subsection D.12 specifies that any necessary rock removal will be done at prevailing wages, currently $1,500 per rock, for a total cost overrun of $1.5 million. But the good news is (and believe me, I had to fight long and hard for this with the board of directors), Corruptocorp has agreed to remove those rocks for only $1,000 apiece! So even though there have been some cost overruns, your smart decisions have saved your taxpayers **half a million dollars**! Give yourselves a round of applause!"*

    *"Now, the other situation is that there has been some 'difficult terrain' as described in subsection 238b, which I'm sure you're all familiar with. And as you know, 'difficult terrain' is not covered by the contract, which is for paving, not for turning mountains into flat roads... (wistful chuckle). Now, technically, according to the contract, we should be charging your town prevailing rates for these sections, but I've worked it so that you will be allowed to re-bid them, if you wish, since our contract doesn't specifically include terrain as described in subsection 238b."*

    Now the contract price has doubled, and Corruptocorp has completely sidestepped all of the difficult and costly work, taking profits only on the easy stuff. The city council members can either admit that they were duped and bought (political suicide), or can simply feed corruptocorp's line to the voters. Which do you think will happen?

    And it gets even worse on smaller scales: look up your local building or electrical inspector. Ten-to-one he is a relative, friend, or campaign donor to the mayor or city council. What's in it for him? Every single construction or home improvement project not only has to pay him a fee, it also has to pass his inspection. Guess which contractors are most likely to pass his inspection? His brothers, friends, family... or the cheapest guy who for some reason has a hard time finding work in this town? Guess how the local inspector feels about homeowner self-improvements: does he think they are a great way for regular people to improve their wealth with a little elbow grease, or does he see them as stealing work from his friends and family?

    The US military is by far the most wasteful customer I've ever had. I'll talk about that if this topic gets any interest.

    edit: as promised, here's the post about military spending:

    http://www.reddit.com/r/Economics/comments/c84bp/how\_realworld\_corruption\_works/c0qrt6i
  • Loss: MatryoshkaLoss with these parameters:
    {
        "loss": "MultipleNegativesRankingLoss",
        "matryoshka_dims": [
            768,
            512,
            256,
            128,
            64
        ],
        "matryoshka_weights": [
            1,
            1,
            1,
            1,
            1
        ],
        "n_dims_per_step": -1
    }
    

Training Hyperparameters

Non-Default Hyperparameters

  • eval_strategy: epoch
  • per_device_eval_batch_size: 4
  • gradient_accumulation_steps: 4
  • learning_rate: 2e-05
  • num_train_epochs: 1
  • lr_scheduler_type: cosine
  • warmup_ratio: 0.1
  • load_best_model_at_end: True
  • optim: adamw_torch_fused
  • batch_sampler: no_duplicates

All Hyperparameters

Click to expand
  • overwrite_output_dir: False
  • do_predict: False
  • eval_strategy: epoch
  • prediction_loss_only: True
  • per_device_train_batch_size: 8
  • per_device_eval_batch_size: 4
  • per_gpu_train_batch_size: None
  • per_gpu_eval_batch_size: None
  • gradient_accumulation_steps: 4
  • eval_accumulation_steps: None
  • learning_rate: 2e-05
  • weight_decay: 0.0
  • adam_beta1: 0.9
  • adam_beta2: 0.999
  • adam_epsilon: 1e-08
  • max_grad_norm: 1.0
  • num_train_epochs: 1
  • max_steps: -1
  • lr_scheduler_type: cosine
  • lr_scheduler_kwargs: {}
  • warmup_ratio: 0.1
  • 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: False
  • 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: False
  • 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: True
  • 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_fused
  • 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: False
  • hub_always_push: False
  • gradient_checkpointing: False
  • gradient_checkpointing_kwargs: None
  • include_inputs_for_metrics: False
  • 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
  • batch_sampler: no_duplicates
  • multi_dataset_batch_sampler: proportional

Training Logs

Epoch Step dim_128_cosine_map@100 dim_256_cosine_map@100 dim_512_cosine_map@100 dim_64_cosine_map@100 dim_768_cosine_map@100
0 0 0.4942 0.5028 0.5322 0.4253 0.5249
0.9231 3 0.4942 0.5028 0.5322 0.4253 0.5249
  • The bold row denotes the saved checkpoint.

Framework Versions

  • Python: 3.10.12
  • Sentence Transformers: 3.0.1
  • Transformers: 4.41.2
  • PyTorch: 2.1.2+cu121
  • Accelerate: 0.31.0
  • Datasets: 2.19.1
  • Tokenizers: 0.19.1

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",
}

MatryoshkaLoss

@misc{kusupati2024matryoshka,
    title={Matryoshka Representation Learning}, 
    author={Aditya Kusupati and Gantavya Bhatt and Aniket Rege and Matthew Wallingford and Aditya Sinha and Vivek Ramanujan and William Howard-Snyder and Kaifeng Chen and Sham Kakade and Prateek Jain and Ali Farhadi},
    year={2024},
    eprint={2205.13147},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

MultipleNegativesRankingLoss

@misc{henderson2017efficient,
    title={Efficient Natural Language Response Suggestion for Smart Reply}, 
    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
    year={2017},
    eprint={1705.00652},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}
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