cjo-ft-v0 / README.md

Add new SentenceTransformer model

c846e6d verified 5 days ago

29 kB

	---
	tags:
	- sentence-transformers
	- sentence-similarity
	- feature-extraction
	- generated_from_trainer
	- dataset_size:154
	- loss:MatryoshkaLoss
	- loss:MultipleNegativesRankingLoss
	base_model: Snowflake/snowflake-arctic-embed-l
	widget:
	- source_sentence: Who will be introducing the first and second Joker movies at the
	festival?
	sentences:
	- '13 Apr 2025Photo: Marshmallow Laser FeastSoil – it’s not something you really
	think about, unless you’re doing the gardening. But this new exhibition at Somerset
	House will change all that, shining a light on its important role in our world,
	including the part it plays in our planet’s future. Top artists, writers and scientists
	from across the globe are all involved in the thought-provoking exploration, which
	aims to stop you thinking of soil as mere dirt and start considering it as something
	far more powerful instead.Read moreBuy ticket24. Enjoy stunning views of the River
	Thames with three courses at Sea ContainersNiall Clutton'
	- favourite movies – the soundtracks. London Soundtrack Festival puts the scores
	front and centre in March 2025, with a series of screenings, talks and performances
	celebrating the musicians who make Hollywood sound so exciting, tense and emotional.
	Highlights include Hildur Guðnadóttir introducing the first and second Joker movies
	and, later in the programme, holding her own concert, David Cronenberg and Howard
	Shore in conversation, screenings of Charlie Chaplin’s Modern Times, The Silence
	of the Lambs and Eighth Grade with live scores, a day-long celebration of video
	game music at The Roundhouse ‘Great Movie Songs with Anne Dudley & Friends’ featuring
	guest appearances from the likes of the Pet Shop Boys’ Neil Tennant and Jake Shears
	of
	- Peter Walker Sculptor and David Harper ComposerSt Paul’s is about to get lit. In
	February, the cathedral will be transformed via a stunning immersive light and
	sound show. ‘Luminous’ by art collective Luxmuralis will animate the interior
	of the building with illuminations and soundscapes inspired by its history, collections
	and archives. Previously, Luxmuralis has created shows at Westminster Abbey, Durham
	Cathedral and Oxford University. The company was also behind the ‘Poppy Fields’
	display at the Tower of London in October.
	- source_sentence: What is the significance of Haddadi in the given context?
	sentences:
	- It’s been almost a decade since Red Bull Culture Clash last took place in London,
	but finally, it’s making its return in 2025, The epic music battle, inspired by
	Jamaican sound clash culture, will see four crews armed with their finest dubplates
	go head-to-head, delivering the best of the electronic, UK rap, Afro, and Caribbean
	music scenes. Only one can be crowned the winner, though, and take home the Red
	Bull Culture Clash trophy, with the victor. The likes of Boy Better Know, A$AP
	Mob and Rebel Sound have previously competed at the legendary competition, as
	well as special guests like J Hus, Stormzy, and Ice Kid, so crowds can expect
	some pretty special things from its return, which takes place at Drumsheds in
	March. Read moreBuy
	- Haddadi
	- The Irish really know how to celebrate, so when it comes to St Patrick’s Day in
	London, the city’s Irish community has no problem showing us how it’s done. A
	day to celebrate the patron saint of Ireland, the occasion is always one big welcoming
	bash. Expect lots of dancing, hearty traditional dishes, a huge parade and as
	many pints as you can handle. The Mayor of London’s annual St Patrick’s Day Festival
	celebration will take place on Sunday March 16 – a day ahead of the official holiday
	– and, as usual, thousands of revellers are expected to watch the parade wend
	its way through central London, while there’ll also be plenty more St Patrick’s
	Day parties and events to check out around the city. We’ll be rounding up the
	best of them for you
	- source_sentence: How does Renée Zellweger's portrayal of Bridget Jones evolve in
	"Mad About the Boy" compared to her earlier performances?
	sentences:
	- "From St Paddy’s to Mothering Sunday, Pancake Day to International Women’s Day, the\
	\ third month of the year packs in a whole host of big celebrations. \nAnd it’s\
	\ also an especially great month for culture vultures. There are a host of film\
	\ festivals happening around the city, from BFI Flare and the inaugural London\
	\ Soundtrack Festival to Kinoteka, Cinema Made in Italy and the Banff Mountain\
	\ Film Festival. \nAnd there’s also Deptford Literature Festival, the Young Barbican\
	\ Takeover Festival, music conference series AVA London and the Other Art Fair. \n\
	Find out about all of these, and much more, in our roundup of the best things\
	\ to do in London over the month."
	- ‘Fourquels’ are usually where film franchises start to flirt with rock bottom,
	so it’s a joy to report that Mad About the Boy is comfortably the best Bridget
	Jones outing since Bridget Jones’s Diary. For Renée Zellweger’s still klutzy but
	now wiser Bridge, living in cosy Hampstead, the singleton Borough era is a distant
	memory. Ciggies and Chardonnay have been dispensed with replaced with a big dose
	of lingering grief for lawyer Mark Darcy (Colin Firth). It says everything for
	the script (co-written by Helen Fielding, Dan Mazer and Abi Morgan) that even
	Daniel Cleaver, now entering his own Jurassic era and a bit sad about it, gets
	an affecting arc here. The plot will surprise no one, but it barely matters –
	this is Bridget’s journey of
	- The Six Nations rugby tournament is back for 2025, taking over boozers, beer gardens
	and outdoor screens across London most weekends up until Saturday March 15. And
	you could just watch on your telly at home. But as the annual competition reaches
	its final stages, you might prefer to catch every scrimmage, try and conversion
	in a lively atmosphere with a nice freshly-poured Guinness in hand. So head to
	one of the rugby pubs, bars, beer halls, markets and social clubs listed here,
	where you’ll find free-flowing pints, special guest appearances and countless
	renditions of ‘Swing Low, Sweet Chariot’.Read moreAdvertising11. Celebrate the
	matriarchs in your life on Motherâ€™s Day in LondonThings to doMums deserve high
	praise all year round,
	- source_sentence: Who is mentioned in relation to getting Guinnesses for the event?
	sentences:
	- 'you agree to our Terms of Use and Privacy Policy and consent to receive emails
	from Time Out about news, events, offers and partner promotions.SubscribeSearchNewsThings
	to DoFood & DrinkArtTheatreTravelHalf-TermOffersSeparatorKidsAttractionsMuseumsFilmMusicNightlifeHotelsLondonLondonNew
	YorkParisChicagoLos AngelesLisbonHong KongSydneyMelbournePortoSingaporeBarcelonaMadridMontrÃ©alBostonMiamiWorldwideCloseNewsThings
	to DoFood & DrinkArtTheatreTravelHalf-TermOffersMoreKidsAttractionsMuseumsFilmMusicNightlifeHotelsLondonLondonNew
	YorkParisChicagoLos AngelesLisbonHong KongSydneyMelbournePortoSingaporeBarcelonaMadridMontrÃ©alBostonMiamiWorldwideSubscribeOffers
	EnglishEnglishEspaÃ±olinstagramtiktokfacebooktwitteryoutubePhotograph: Steve Beech
	/'
	- Haddadi
	- 'Shields returning.Read moreBuy ticket2. Get the Guinnesses in for St Patrickâ€™s
	Day in LondonThings to doPhotograph: Sandor Szmutko'
	- source_sentence: What platforms are mentioned in the context for social media engagement?
	sentences:
	- out for your first newsletter in your inbox soon!instagramtiktokfacebooktwitteryoutubeAbout
	usPress officeInvestor relationsOur awardsWork for Time OutEditorial guidelinesPrivacy
	noticeDo not sell my informationCookie policyAccessibility statementTerms of useModern
	slavery statementManage cookiesContact usGet ListedClaim your listingTime Out
	Offers FAQAdvertisingTime Out MarketTime Out productsTime Out OffersTime Out WorldwideMoviesRestaurantsSite
	MapÂ© 2025 Time Out England Limited and affiliated companies owned by Time Out
	Group Plc. All rights reserved. Time Out is a registered trademark of Time Out
	Digital Limited.
	- 'You’ve probably heard all about Versailles’ dazzling Hall of Mirrors and its
	gorgeous, well-manicured gardens – maybe you’ve even seen them IRL. But do you
	know about the role the French royal court played in not just spreading scientific
	knowledge, but making it fashionable, too? The Science Museum’s latest exhibition,
	‘Versailles: Science And Splendour’, will uncover that lesser-talked-about side
	of the palace’s history, diving into the royal family’s relationship with science,
	women’s impact on medicine, philosophy and botany at the royal court, and showcasing
	more than 100 items that reinforce those stories – many of which have never been
	displayed in the UK before.'
	- 'Steve Beech / ShutterstockPhotograph: Steve Beech / ShutterstockLondon events
	in March 2025Our guide to the best events, festivals, workshops, exhibitions and
	things to do throughout March 2025 in LondonWednesday 12 February 2025ShareCopy
	LinkFacebookTwitterPinterestEmailWhatsAppWritten by Rosie HewitsonThings to Do
	Editor, LondonAdvertisingThe days are getting gradually lighter, the snowdrops
	and crocuses have arrived in London’s park, and London’s cultural scene has burst
	into life after a mid-winter lull. It can only mean one thing; March is right
	around the corner.'
	pipeline_tag: sentence-similarity
	library_name: sentence-transformers
	metrics:
	- cosine_accuracy@1
	- cosine_accuracy@3
	- cosine_accuracy@5
	- cosine_accuracy@10
	- cosine_precision@1
	- cosine_precision@3
	- cosine_precision@5
	- cosine_precision@10
	- cosine_recall@1
	- cosine_recall@3
	- cosine_recall@5
	- cosine_recall@10
	- cosine_ndcg@10
	- cosine_mrr@10
	- cosine_map@100
	model-index:
	- name: SentenceTransformer based on Snowflake/snowflake-arctic-embed-l
	results:
	- task:
	type: information-retrieval
	name: Information Retrieval
	dataset:
	name: Unknown
	type: unknown
	metrics:
	- type: cosine_accuracy@1
	value: 0.8846153846153846
	name: Cosine Accuracy@1
	- type: cosine_accuracy@3
	value: 1.0
	name: Cosine Accuracy@3
	- type: cosine_accuracy@5
	value: 1.0
	name: Cosine Accuracy@5
	- type: cosine_accuracy@10
	value: 1.0
	name: Cosine Accuracy@10
	- type: cosine_precision@1
	value: 0.8846153846153846
	name: Cosine Precision@1
	- type: cosine_precision@3
	value: 0.33333333333333337
	name: Cosine Precision@3
	- type: cosine_precision@5
	value: 0.20000000000000004
	name: Cosine Precision@5
	- type: cosine_precision@10
	value: 0.10000000000000002
	name: Cosine Precision@10
	- type: cosine_recall@1
	value: 0.8846153846153846
	name: Cosine Recall@1
	- type: cosine_recall@3
	value: 1.0
	name: Cosine Recall@3
	- type: cosine_recall@5
	value: 1.0
	name: Cosine Recall@5
	- type: cosine_recall@10
	value: 1.0
	name: Cosine Recall@10
	- type: cosine_ndcg@10
	value: 0.9574149715659375
	name: Cosine Ndcg@10
	- type: cosine_mrr@10
	value: 0.9423076923076923
	name: Cosine Mrr@10
	- type: cosine_map@100
	value: 0.9423076923076923
	name: Cosine Map@100
	---

	# SentenceTransformer based on Snowflake/snowflake-arctic-embed-l

	This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Snowflake/snowflake-arctic-embed-l](https://huggingface.co/Snowflake/snowflake-arctic-embed-l). 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: [Snowflake/snowflake-arctic-embed-l](https://huggingface.co/Snowflake/snowflake-arctic-embed-l) <!-- at revision d8fb21ca8d905d2832ee8b96c894d3298964346b -->
	- Maximum Sequence Length: 512 tokens
	- Output Dimensionality: 1024 dimensions
	- Similarity Function: Cosine Similarity
	<!-- - Training Dataset: Unknown -->
	<!-- - Language: Unknown -->
	<!-- - License: Unknown -->

	### Model Sources

	- Documentation: [Sentence Transformers Documentation](https://sbert.net)
	- Repository: [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
	- Hugging Face: [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)

	### Full Model Architecture

	```
	SentenceTransformer(
	(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel
	(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:

	```bash
	pip install -U sentence-transformers
	```

	Then you can load this model and run inference.
	```python
	from sentence_transformers import SentenceTransformer

	# Download from the 🤗 Hub
	model = SentenceTransformer("ric9176/cjo-ft-v0")
	# Run inference
	sentences = [
	'What platforms are mentioned in the context for social media engagement?',
	'out for your first newsletter in your inbox soon!instagramtiktokfacebooktwitteryoutubeAbout usPress officeInvestor relationsOur awardsWork for Time OutEditorial guidelinesPrivacy noticeDo not sell my informationCookie policyAccessibility statementTerms of useModern slavery statementManage cookiesContact usGet ListedClaim your listingTime Out Offers FAQAdvertisingTime Out MarketTime Out productsTime Out OffersTime Out WorldwideMoviesRestaurantsSite MapÂ© 2025 Time Out England Limited and affiliated companies owned by Time Out Group Plc. All rights reserved. Time Out is a registered trademark of Time Out Digital Limited.',
	'Steve Beech / ShutterstockPhotograph: Steve Beech / ShutterstockLondon events in March 2025Our guide to the best events, festivals, workshops, exhibitions and things to do throughout March 2025 in LondonWednesday 12 February 2025ShareCopy LinkFacebookTwitterPinterestEmailWhatsAppWritten by Rosie HewitsonThings to Do Editor, LondonAdvertisingThe days are getting gradually lighter, the snowdrops and crocuses have arrived in London’s park, and London’s cultural scene has burst into life after a mid-winter lull. It can only mean one thing; March is right around the corner.',
	]
	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]
	```

	<!--
	### Direct Usage (Transformers)

	<details><summary>Click to see the direct usage in Transformers</summary>

	</details>
	-->

	<!--
	### Downstream Usage (Sentence Transformers)

	You can finetune this model on your own dataset.

	<details><summary>Click to expand</summary>

	</details>
	-->

	<!--
	### Out-of-Scope Use

	List how the model may foreseeably be misused and address what users ought not to do with the model.
	-->

	## Evaluation

	### Metrics

	#### Information Retrieval

	* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)

	\| Metric \| Value \|
	\|:--------------------\|:-----------\|
	\| cosine_accuracy@1 \| 0.8846 \|
	\| cosine_accuracy@3 \| 1.0 \|
	\| cosine_accuracy@5 \| 1.0 \|
	\| cosine_accuracy@10 \| 1.0 \|
	\| cosine_precision@1 \| 0.8846 \|
	\| cosine_precision@3 \| 0.3333 \|
	\| cosine_precision@5 \| 0.2 \|
	\| cosine_precision@10 \| 0.1 \|
	\| cosine_recall@1 \| 0.8846 \|
	\| cosine_recall@3 \| 1.0 \|
	\| cosine_recall@5 \| 1.0 \|
	\| cosine_recall@10 \| 1.0 \|
	\| cosine_ndcg@10 \| 0.9574 \|
	\| cosine_mrr@10 \| 0.9423 \|
	\| cosine_map@100 \| 0.9423 \|

	<!--
	## Bias, Risks and Limitations

	What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.
	-->

	<!--
	### Recommendations

	What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.
	-->

	## Training Details

	### Training Dataset

	#### Unnamed Dataset

	* Size: 154 training samples
	* Columns: <code>sentence_0</code> and <code>sentence_1</code>
	* Approximate statistics based on the first 154 samples:
	\| \| sentence_0 \| sentence_1 \|
	\|:--------\|:----------------------------------------------------------------------------------\|:------------------------------------------------------------------------------------\|
	\| type \| string \| string \|
	\| details \| <ul><li>min: 8 tokens</li><li>mean: 18.04 tokens</li><li>max: 30 tokens</li></ul> \| <ul><li>min: 5 tokens</li><li>mean: 129.57 tokens</li><li>max: 226 tokens</li></ul> \|
	* Samples:
	\| sentence_0 \| sentence_1 \|
	\|:-----------------------------------------------------------------------------------------------------------\|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\|
	\| <code>What types of events and activities are highlighted for the weekend in London?</code> \| <code>30 Wonderful Things To Do This Weekend in London â€“ weekend events and activities in LondonGo to the contentGo to the footerNo thanksSubscribeðŸ™ŒAwesome, you're subscribed!Thanks for subscribing! Look out for your first newsletter in your inbox soon!Get us in your inboxSign up to our newsletter for the latest and greatest from your city and beyondEnter email addressDÃ©jÃ vu! We already have this email. Try another?By entering your email address you agree to our Terms of Use and Privacy Policy and consent to receive emails from Time Out about news, events, offers and partner promotions.No thanks Awesome, you're subscribed!Thanks for subscribing! Look out for your first newsletter in your inbox soon!The best of London for free.Sign up for</code> \|
	\| <code>How can individuals stay updated on the latest happenings in London according to the context?</code> \| <code>30 Wonderful Things To Do This Weekend in London â€“ weekend events and activities in LondonGo to the contentGo to the footerNo thanksSubscribeðŸ™ŒAwesome, you're subscribed!Thanks for subscribing! Look out for your first newsletter in your inbox soon!Get us in your inboxSign up to our newsletter for the latest and greatest from your city and beyondEnter email addressDÃ©jÃ vu! We already have this email. Try another?By entering your email address you agree to our Terms of Use and Privacy Policy and consent to receive emails from Time Out about news, events, offers and partner promotions.No thanks Awesome, you're subscribed!Thanks for subscribing! Look out for your first newsletter in your inbox soon!The best of London for free.Sign up for</code> \|
	\| <code>What benefits do subscribers receive by signing up for the email newsletter?</code> \| <code>free.Sign up for our email to enjoy London without spending a thing (as well as some options when youâ€™re feeling flush).Enter email addressDÃ©jÃ vu! We already have this email. Try another?No thanksBy entering your email address you agree to our Terms of Use and Privacy Policy and consent to receive emails from Time Out about news, events, offers and partner promotions.No thanks Awesome, you're subscribed!Thanks for subscribing! Look out for your first newsletter in your inbox soon!Love the mag?Our newsletter hand-delivers the best bits to your inbox. Sign up to unlock our digital magazines and also receive the latest news, events, offers and partner promotions.Enter email addressDÃ©jÃ vu! We already have this email. Try another?No</code> \|
	* Loss: [<code>MatryoshkaLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshkaloss) with these parameters:
	```json
	{
	"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`: steps
	- `per_device_train_batch_size`: 10
	- `per_device_eval_batch_size`: 10
	- `num_train_epochs`: 10
	- `multi_dataset_batch_sampler`: round_robin

	#### All Hyperparameters
	<details><summary>Click to expand</summary>

	- `overwrite_output_dir`: False
	- `do_predict`: False
	- `eval_strategy`: steps
	- `prediction_loss_only`: True
	- `per_device_train_batch_size`: 10
	- `per_device_eval_batch_size`: 10
	- `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`: 5e-05
	- `weight_decay`: 0.0
	- `adam_beta1`: 0.9
	- `adam_beta2`: 0.999
	- `adam_epsilon`: 1e-08
	- `max_grad_norm`: 1
	- `num_train_epochs`: 10
	- `max_steps`: -1
	- `lr_scheduler_type`: linear
	- `lr_scheduler_kwargs`: {}
	- `warmup_ratio`: 0.0
	- `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`: 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`: batch_sampler
	- `multi_dataset_batch_sampler`: round_robin

	</details>

	### Training Logs
	\| Epoch \| Step \| cosine_ndcg@10 \|
	\|:-----:\|:----:\|:--------------:\|
	\| 1.0 \| 16 \| 0.9213 \|
	\| 2.0 \| 32 \| 0.9355 \|
	\| 3.0 \| 48 \| 0.9290 \|
	\| 3.125 \| 50 \| 0.9432 \|
	\| 4.0 \| 64 \| 0.9574 \|
	\| 5.0 \| 80 \| 0.9574 \|
	\| 6.0 \| 96 \| 0.9574 \|
	\| 6.25 \| 100 \| 0.9574 \|
	\| 7.0 \| 112 \| 0.9574 \|
	\| 8.0 \| 128 \| 0.9574 \|
	\| 9.0 \| 144 \| 0.9574 \|
	\| 9.375 \| 150 \| 0.9574 \|
	\| 10.0 \| 160 \| 0.9574 \|


	### Framework Versions
	- Python: 3.11.11
	- Sentence Transformers: 3.4.1
	- Transformers: 4.48.3
	- PyTorch: 2.5.1+cu124
	- Accelerate: 1.3.0
	- Datasets: 3.3.2
	- Tokenizers: 0.21.0

	## Citation

	### BibTeX

	#### Sentence Transformers
	```bibtex
	@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
	```bibtex
	@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
	```bibtex
	@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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