checkpoint-309/README.md

metadata

base_model: bobox/DeBERTa-small-ST-v1-test-step3
datasets: []
language: []
library_name: sentence-transformers
metrics:
  - pearson_cosine
  - spearman_cosine
  - pearson_manhattan
  - spearman_manhattan
  - pearson_euclidean
  - spearman_euclidean
  - pearson_dot
  - spearman_dot
  - pearson_max
  - spearman_max
pipeline_tag: sentence-similarity
tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:163205
  - loss:CachedGISTEmbedLoss
widget:
  - source_sentence: interview question on why you want to leave your current job?
    sentences:
      - >-
        Carrier proteins bind and carry the molecules across the cell membrane.
        These proteins bind a molecule on one side of the membrane, change shape
        as they carry the molecule across the membrane, and deposit the molecule
        on the other side of the membrane. Even though a protein is involved in
        both these methods of transport, neither method requires energy.
        Therefore these are still types of passive transport.
      - >-
        ['Desire to learn.', 'Desire to take on more responsibility.', 'Desire
        to take on less responsibility.', 'Desire to relocate.', 'Desire for a
        career change.', 'Desire to gain a new skill or grow a current skill.',
        'Company reorganization has led to change in job content.']
      - >-
        The small intestine is a narrow tube that starts at the stomach and ends
        at the large intestine. In adults, it’s about 7 meters (23 feet) long.
        Most chemical digestion and almost all nutrient absorption take place in
        the small intestine.
  - source_sentence: >-
      They say a number of people from the Mujahideen-e-Khalq (MEK) group were
      injured at Camp Liberty in Baghdad.

      Baghdad has in the past repeatedly denied attacking the group.

      MEK members fought with Iraq against Iran in the 1980s, but have since
      fallen out with the current Iraqi government.

      In an emailed message, the Paris-based National Council of Resistance of
      Iran (NCRI), the MEK's parent group, said dozens of missiles hit the camp
      on Thursday evening.

      It said two residents were killed and a third later died in hospital of
      his wounds.

      The US condemned the attack "in the strongest terms" and urged Iraq to
      better protect the camp.

      An Iranian-backed Shia militia, al-Mukhtar Army, said it had fired rockets
      at the camp, Reuters news agency reported.

      The camp is located in a former US military base, near Baghdad's airport.

      The Iraqi authorities have made no public comments on the report. However,
      one security official was quoted by the Associated Press as saying four
      rockets hit the camp, injuring two people.

      In September, the MEK accused Iraqi forces of attacking Camp Ashraf
      north-east of Baghdad and killing 52 of the group's members.

      In recent years, Baghdad has been trying to dismantle MEK camps and eject
      the group.

      Iran considers the MEK a terrorist group.

      The group was removed from the US state department's list of terrorist
      organisations last year.
    sentences:
      - >-
        A rocket attack has killed three members of an Iranian opposition group
        in Iraq, the group and its parent organisation say.
      - >-
        Directions See How It's Made. 1  Preheat the oven to 375 degrees. 2 
        Heat a large skillet over medium heat. 3  Add the spinach.  Spread the
        spinach mixture evenly on the bottom of the prepared baking 1  dish.
        Bake until the egg whites are set, about 25 minutes.  Let the casserole
        sit for about 5 minutes, and then cut into pieces and 1  serve. Submit a
        Correction.
      - >-
        Toll free phone number: 011-44-871-246-0002. Ryan Airlines
        www.ryanair.com is a low-fare airlines headquartered in Dublin, Ireland.
        Transporting over 103 million passengers last year there are 1600 daily
        flights with 185 destinations. The Ryan fleet consists of 300 new Boeing
        737-800 aircraft in operation with 283 738 aircraft on order.
  - source_sentence: In what unit is heat measured in?
    sentences:
      - >-
        The heat that is either absorbed or released is measured in joules. The
        mass is measured in grams. The change in temperature is given by , where
        is the final temperature and is the initial temperature.
      - >-
        The nitrogen atom of a primary amine is bonded to two hydrogen atoms and
        one carbon. The nitrogen atom of a secondary amine is bonded to one
        hydrogen and two carbons. The nitrogen atom of a tertiary amine is
        bonded to three carbon atoms. Amines are typically named by a common
        system rather than by IUPAC guidelines. The common system for naming
        amines along with several examples is shown below.
      - >-
        Seattle Symphony Live @ Benaroya Hall — Windborne's The Music of David
        Bowie: A Rock Symphony with the Seattle Symphony Tuesday, 10 January,
        2017 7:30PM Join conductor Brent Havens and a full rock band on a
        symphonic musical odyssey that explores the incredible range of David
        Bowie’s Music.
  - source_sentence: meristematic tissue definition
    sentences:
      - >-
        In this chapter, you saw how pressure and buoyancy of fluids can be used
        to make work easier — from raising a car on a lift to floating a ship on
        the ocean. Devices that make work easier are called machines in physics.
      - A Land Rover is splashing water as it crosses a river.
      - "meristem. n. 1. (Botany) a plant tissue responsible for growth, whose cells divide and differentiate to form the tissues and organs of the plant. Meristems occur within the stem (see cambium) and leaves and at the tips of stems and roots. [C19: from Greek meristos divided, from merizein to divide, from meris portion]. (Ë\x88mÉ\x9Br É\x99Ë\x8CstÉ\x9Bm)."
  - source_sentence: >-
      More than 190 countries and territories around the world had confirmed
      coronavirus cases by March 22 , 2020 .
    sentences:
      - when electricity flows to a light bulb , the light bulb will come on
      - >-
        As of 22 March , more than 337,000 cases of COVID-19 have been reported
        in over 190 countries and territories , resulting in more than 14,400
        deaths and 96,000 recoveries .
      - a greenhouse is used to protect plants by keeping them warm
model-index:
  - name: SentenceTransformer based on bobox/DeBERTa-small-ST-v1-test-step3
    results:
      - task:
          type: semantic-similarity
          name: Semantic Similarity
        dataset:
          name: sts test
          type: sts-test
        metrics:
          - type: pearson_cosine
            value: 0.8767817266460346
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.9032290290662617
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.9065146784679962
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.9035283702537087
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.9070553577944469
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.9039456310149221
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.8544828510438696
            name: Pearson Dot
          - type: spearman_dot
            value: 0.8599922398628699
            name: Spearman Dot
          - type: pearson_max
            value: 0.9070553577944469
            name: Pearson Max
          - type: spearman_max
            value: 0.9039456310149221
            name: Spearman Max

SentenceTransformer based on bobox/DeBERTa-small-ST-v1-test-step3

This is a sentence-transformers model finetuned from bobox/DeBERTa-small-ST-v1-test-step3 on the bobox/enhanced_nli-50_k dataset. 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: bobox/DeBERTa-small-ST-v1-test-step3
• Maximum Sequence Length: 512 tokens
• Output Dimensionality: 768 tokens
• Similarity Function: Cosine Similarity
• Training Dataset:
  • bobox/enhanced_nli-50_k

Model Sources

• Documentation: Sentence Transformers Documentation
• Repository: Sentence Transformers on GitHub
• Hugging Face: Sentence Transformers on Hugging Face

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: DebertaV2Model 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
)

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("bobox/DeBERTa-small-ST-v1-test-UnifiedDatasets-Ft-checkpoints-tmp")
# Run inference
sentences = [
    'More than 190 countries and territories around the world had confirmed coronavirus cases by March 22 , 2020 .',
    'As of 22 March , more than 337,000 cases of COVID-19 have been reported in over 190 countries and territories , resulting in more than 14,400 deaths and 96,000 recoveries .',
    'a greenhouse is used to protect plants by keeping them warm',
]
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

Semantic Similarity

• Dataset: sts-test
• Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.8768
spearman_cosine	0.9032
pearson_manhattan	0.9065
spearman_manhattan	0.9035
pearson_euclidean	0.9071
spearman_euclidean	0.9039
pearson_dot	0.8545
spearman_dot	0.86
pearson_max	0.9071
spearman_max	0.9039

Training Details

Training Dataset

bobox/enhanced_nli-50_k

• Dataset: bobox/enhanced_nli-50_k
• Size: 163,205 training samples
• Columns: sentence1 and sentence2
• Approximate statistics based on the first 1000 samples:

  	sentence1	sentence2
  type	string	string
  details	min: 4 tokens mean: 36.63 tokens max: 370 tokens	min: 2 tokens mean: 54.93 tokens max: 363 tokens

• Samples:

  sentence1	sentence2
  apple customer number	Apple Customer Service. 800-676-2775. Before dialing Apple Customer Service. We've tried for years to eliminate that 44 minute wait for you. But the fact is that it can still take many phone calls to Apple to resolve your issue. Now you can hire GetHuman to do all the work on the phone for you.
  Molly 's Game grossed more than $ 28.5 million in the US and Canada and less than $ 24.65 in other countries .	, Molly 's Game has grossed $ 28.8 million in the United States and Canada , and $ 24.6 million in other territories , for a worldwide total of $ 53.4 million .
  mawk definition	Definitions for mawk. Here are all the possible meanings and translations of the word mawk. Wiktionary(0.00 / 0 votes)Rate this definition: Origin: From mawk, mauk, a contraction of mathek, from maðkr, a diminutive of a base from maþa- (Old English maþa), from Indo-European *math-, moth- used in reference to insects and vermin. Cognate with Danish madike, Swedish mask, archaic English maddock (modern maggot).

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) 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()
  ), 'temperature': 0.025}
  

Evaluation Dataset

bobox/enhanced_nli-50_k

• Dataset: bobox/enhanced_nli-50_k
• Size: 3,052 evaluation samples
• Columns: sentence1 and sentence2
• Approximate statistics based on the first 1000 samples:

  	sentence1	sentence2
  type	string	string
  details	min: 4 tokens mean: 33.13 tokens max: 313 tokens	min: 2 tokens mean: 58.53 tokens max: 422 tokens

• Samples:

  sentence1	sentence2
  Dwight Beare, 27, from Melbourne, Australia, was killed in the crash near to the 16th milestone on the TT course on the Isle of Man. Mr Beare suffered fatal spine and back injuries on the west of the island on 4 June at about 14:10 BST. A verdict of misadventure was recorded by Coroner John Needham at Douglas Court House earlier. Mr Needham said: "I am not in a position to give an exact reason for the loss of control but Mr Beare would have died almost instantaneously". The inquest heard from a witness who said the carpenter and his passenger, Benjamin Binns, were thrown into the air after their vehicle hit the road side. Mr Binns, who was airlifted to hospital with a broken leg, said before the race both he and Mr Beare had been "excited and confident". "I will miss my friend dearly and his memory will live on," he said. No defects were found on the vehicle. Mr Beare moved to Onchan on the Isle of Man to pursue his road racing passion. He made his TT debut in 2014 finishing 12th in the second race of the week, with his father Noel as his passenger. He returned in 2015 when he came 17th.	A TT racer died after being thrown from his sidecar when he hit the side of a road, an inquest has heard.
  are yeezy adidas or nike?	Adidas Yeezy is a fashion collaboration between the German sportswear brand Adidas and American designer Kanye West. The collaboration has become notable for its high-end sneakers, and the Yeezy Boost sneaker line has been considered one of the most influential sneaker brands in the world.
  what remains are changed into natural gas by heat and pressure change?	heat and pressure change the remains of prehistoric living things into natural gas. Dinosaurs and Other Prehistoric Creatures Dinosaurs are just one group of prehistoric animals. heat and pressure change the remains of dinosaurs into natural gas

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) 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()
  ), 'temperature': 0.025}
  

Training Hyperparameters

Non-Default Hyperparameters

• eval_strategy: steps
• per_device_train_batch_size: 320
• per_device_eval_batch_size: 128
• learning_rate: 2e-05
• weight_decay: 0.0001
• num_train_epochs: 2
• lr_scheduler_type: cosine_with_restarts
• lr_scheduler_kwargs: {'num_cycles': 3}
• warmup_ratio: 0.25
• save_safetensors: False
• fp16: True
• push_to_hub: True
• hub_model_id: bobox/DeBERTa-small-ST-v1-test-UnifiedDatasets-Ft-checkpoints-tmp
• hub_strategy: all_checkpoints
• batch_sampler: no_duplicates

All Hyperparameters

Click to expand

• overwrite_output_dir: False
• do_predict: False
• eval_strategy: steps
• prediction_loss_only: True
• per_device_train_batch_size: 320
• per_device_eval_batch_size: 128
• 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: 2e-05
• weight_decay: 0.0001
• adam_beta1: 0.9
• adam_beta2: 0.999
• adam_epsilon: 1e-08
• max_grad_norm: 1.0
• num_train_epochs: 2
• max_steps: -1
• lr_scheduler_type: cosine_with_restarts
• lr_scheduler_kwargs: {'num_cycles': 3}
• warmup_ratio: 0.25
• warmup_steps: 0
• log_level: passive
• log_level_replica: warning
• log_on_each_node: True
• logging_nan_inf_filter: True
• save_safetensors: False
• 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: True
• 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: True
• resume_from_checkpoint: None
• hub_model_id: bobox/DeBERTa-small-ST-v1-test-UnifiedDatasets-Ft-checkpoints-tmp
• hub_strategy: all_checkpoints
• 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
• eval_on_start: False
• eval_use_gather_object: False
• batch_sampler: no_duplicates
• multi_dataset_batch_sampler: proportional

Training Logs

Click to expand

Epoch	Step	Training Loss	loss	sts-test_spearman_cosine
0.0020	1	0.107	-	-
0.0039	2	0.1529	-	-
0.0059	3	0.1874	-	-
0.0078	4	0.1682	-	-
0.0098	5	0.1438	0.1470	0.9078
0.0117	6	0.2961	-	-
0.0137	7	0.3019	-	-
0.0157	8	0.1184	-	-
0.0176	9	0.3176	-	-
0.0196	10	0.2234	0.1468	0.9078
0.0215	11	0.1881	-	-
0.0235	12	0.1593	-	-
0.0254	13	0.1833	-	-
0.0274	14	0.1352	-	-
0.0294	15	0.3143	0.1462	0.9077
0.0313	16	0.1583	-	-
0.0333	17	0.2015	-	-
0.0352	18	0.1476	-	-
0.0372	19	0.1676	-	-
0.0391	20	0.1525	0.1454	0.9079
0.0411	21	0.1717	-	-
0.0431	22	0.198	-	-
0.0450	23	0.3062	-	-
0.0470	24	0.1241	-	-
0.0489	25	0.1087	0.1446	0.9082
0.0509	26	0.1767	-	-
0.0528	27	0.1951	-	-
0.0548	28	0.1621	-	-
0.0568	29	0.221	-	-
0.0587	30	0.2241	0.1435	0.9083
0.0607	31	0.2093	-	-
0.0626	32	0.1615	-	-
0.0646	33	0.1615	-	-
0.0665	34	0.1772	-	-
0.0685	35	0.2324	0.1423	0.9084
0.0705	36	0.2611	-	-
0.0724	37	0.214	-	-
0.0744	38	0.1985	-	-
0.0763	39	0.1855	-	-
0.0783	40	0.1234	0.1410	0.9085
0.0802	41	0.1492	-	-
0.0822	42	0.2022	-	-
0.0841	43	0.2146	-	-
0.0861	44	0.1688	-	-
0.0881	45	0.175	0.1396	0.9087
0.0900	46	0.2123	-	-
0.0920	47	0.1118	-	-
0.0939	48	0.3009	-	-
0.0959	49	0.1071	-	-
0.0978	50	0.2608	0.1382	0.9085
0.0998	51	0.1368	-	-
0.1018	52	0.2307	-	-
0.1037	53	0.1366	-	-
0.1057	54	0.1857	-	-
0.1076	55	0.2155	0.1367	0.9085
0.1096	56	0.2022	-	-
0.1115	57	0.2076	-	-
0.1135	58	0.4133	-	-
0.1155	59	0.1823	-	-
0.1174	60	0.1136	0.1353	0.9088
0.1194	61	0.1687	-	-
0.1213	62	0.1591	-	-
0.1233	63	0.1653	-	-
0.1252	64	0.1799	-	-
0.1272	65	0.1578	0.1337	0.9090
0.1292	66	0.1844	-	-
0.1311	67	0.1489	-	-
0.1331	68	0.1845	-	-
0.1350	69	0.1364	-	-
0.1370	70	0.1584	0.1321	0.9086
0.1389	71	0.2279	-	-
0.1409	72	0.2028	-	-
0.1429	73	0.2291	-	-
0.1448	74	0.2419	-	-
0.1468	75	0.1329	0.1306	0.9083
0.1487	76	0.204	-	-
0.1507	77	0.2239	-	-
0.1526	78	0.2181	-	-
0.1546	79	0.1285	-	-
0.1566	80	0.1067	0.1292	0.9079
0.1585	81	0.1189	-	-
0.1605	82	0.236	-	-
0.1624	83	0.1584	-	-
0.1644	84	0.1925	-	-
0.1663	85	0.129	0.1278	0.9079
0.1683	86	0.1376	-	-
0.1703	87	0.1691	-	-
0.1722	88	0.1045	-	-
0.1742	89	0.165	-	-
0.1761	90	0.2926	0.1267	0.9076
0.1781	91	0.1048	-	-
0.1800	92	0.1596	-	-
0.1820	93	0.2474	-	-
0.1840	94	0.1652	-	-
0.1859	95	0.2483	0.1253	0.9076
0.1879	96	0.1623	-	-
0.1898	97	0.1955	-	-
0.1918	98	0.2023	-	-
0.1937	99	0.1886	-	-
0.1957	100	0.1284	0.1229	0.9079
0.1977	101	0.2005	-	-
0.1996	102	0.2301	-	-
0.2016	103	0.2249	-	-
0.2035	104	0.214	-	-
0.2055	105	0.1429	0.1208	0.9077
0.2074	106	0.17	-	-
0.2094	107	0.1955	-	-
0.2114	108	0.1964	-	-
0.2133	109	0.1246	-	-
0.2153	110	0.1295	0.1190	0.9072
0.2172	111	0.2203	-	-
0.2192	112	0.2195	-	-
0.2211	113	0.1823	-	-
0.2231	114	0.174	-	-
0.2250	115	0.207	0.1175	0.9069
0.2270	116	0.2156	-	-
0.2290	117	0.2202	-	-
0.2309	118	0.2718	-	-
0.2329	119	0.1387	-	-
0.2348	120	0.1506	0.1168	0.9069
0.2368	121	0.1185	-	-
0.2387	122	0.1681	-	-
0.2407	123	0.2321	-	-
0.2427	124	0.1457	-	-
0.2446	125	0.2027	0.1165	0.9071
0.2466	126	0.1821	-	-
0.2485	127	0.1258	-	-
0.2505	128	0.184	-	-
0.2524	129	0.2015	-	-
0.2544	130	0.1323	0.1154	0.9074
0.2564	131	0.1939	-	-
0.2583	132	0.1428	-	-
0.2603	133	0.1063	-	-
0.2622	134	0.1602	-	-
0.2642	135	0.1814	0.1139	0.9067
0.2661	136	0.1518	-	-
0.2681	137	0.1379	-	-
0.2701	138	0.1708	-	-
0.2720	139	0.2046	-	-
0.2740	140	0.1259	0.1124	0.9063
0.2759	141	0.1181	-	-
0.2779	142	0.2144	-	-
0.2798	143	0.1822	-	-
0.2818	144	0.1667	-	-
0.2838	145	0.0779	0.1118	0.9060
0.2857	146	0.147	-	-
0.2877	147	0.1913	-	-
0.2896	148	0.1357	-	-
0.2916	149	0.1128	-	-
0.2935	150	0.0996	0.1113	0.9054
0.2955	151	0.1956	-	-
0.2975	152	0.0942	-	-
0.2994	153	0.1406	-	-
0.3014	154	0.2868	-	-
0.3033	155	0.1102	0.1114	0.9048
0.3053	156	0.1659	-	-
0.3072	157	0.1645	-	-
0.3092	158	0.151	-	-
0.3112	159	0.158	-	-
0.3131	160	0.2323	0.1113	0.9048
0.3151	161	0.1157	-	-
0.3170	162	0.1507	-	-
0.3190	163	0.1879	-	-
0.3209	164	0.143	-	-
0.3229	165	0.2227	0.1116	0.9050
0.3249	166	0.1624	-	-
0.3268	167	0.1345	-	-
0.3288	168	0.1765	-	-
0.3307	169	0.1368	-	-
0.3327	170	0.0962	0.1113	0.9056
0.3346	171	0.1783	-	-
0.3366	172	0.2019	-	-
0.3386	173	0.1761	-	-
0.3405	174	0.1855	-	-
0.3425	175	0.1922	0.1106	0.9054
0.3444	176	0.1538	-	-
0.3464	177	0.1049	-	-
0.3483	178	0.1619	-	-
0.3503	179	0.0731	-	-
0.3523	180	0.1205	0.1097	0.9059
0.3542	181	0.169	-	-
0.3562	182	0.1688	-	-
0.3581	183	0.1274	-	-
0.3601	184	0.1477	-	-
0.3620	185	0.1418	0.1094	0.9055
0.3640	186	0.2477	-	-
0.3659	187	0.1713	-	-
0.3679	188	0.1703	-	-
0.3699	189	0.1176	-	-
0.3718	190	0.1811	0.1084	0.9048
0.3738	191	0.162	-	-
0.3757	192	0.1141	-	-
0.3777	193	0.154	-	-
0.3796	194	0.2461	-	-
0.3816	195	0.1573	0.1076	0.9046
0.3836	196	0.1197	-	-
0.3855	197	0.1395	-	-
0.3875	198	0.0847	-	-
0.3894	199	0.1848	-	-
0.3914	200	0.1377	0.1072	0.9047
0.3933	201	0.1109	-	-
0.3953	202	0.1051	-	-
0.3973	203	0.0975	-	-
0.3992	204	0.127	-	-
0.4012	205	0.1297	0.1069	0.9049
0.4031	206	0.0783	-	-
0.4051	207	0.053	-	-
0.4070	208	0.1916	-	-
0.4090	209	0.178	-	-
0.4110	210	0.2343	0.1067	0.9053
0.4129	211	0.1816	-	-
0.4149	212	0.2522	-	-
0.4168	213	0.1787	-	-
0.4188	214	0.1913	-	-
0.4207	215	0.175	0.1055	0.9056
0.4227	216	0.1533	-	-
0.4247	217	0.1819	-	-
0.4266	218	0.2541	-	-
0.4286	219	0.1103	-	-
0.4305	220	0.1693	0.1040	0.9062
0.4325	221	0.1233	-	-
0.4344	222	0.0922	-	-
0.4364	223	0.1243	-	-
0.4384	224	0.1613	-	-
0.4403	225	0.1188	0.1030	0.9065
0.4423	226	0.196	-	-
0.4442	227	0.2254	-	-
0.4462	228	0.1162	-	-
0.4481	229	0.2579	-	-
0.4501	230	0.1203	0.1029	0.9071
0.4521	231	0.1654	-	-
0.4540	232	0.1808	-	-
0.4560	233	0.1397	-	-
0.4579	234	0.2177	-	-
0.4599	235	0.162	0.1040	0.9078
0.4618	236	0.177	-	-
0.4638	237	0.0556	-	-
0.4658	238	0.2285	-	-
0.4677	239	0.1657	-	-
0.4697	240	0.2555	0.1053	0.9077
0.4716	241	0.1606	-	-
0.4736	242	0.1257	-	-
0.4755	243	0.1898	-	-
0.4775	244	0.1621	-	-
0.4795	245	0.1606	0.1054	0.9079
0.4814	246	0.0983	-	-
0.4834	247	0.2028	-	-
0.4853	248	0.0997	-	-
0.4873	249	0.1582	-	-
0.4892	250	0.2394	0.1052	0.9074
0.4912	251	0.2186	-	-
0.4932	252	0.0993	-	-
0.4951	253	0.1805	-	-
0.4971	254	0.1178	-	-
0.4990	255	0.2198	0.1043	0.9070
0.5010	256	0.1064	-	-
0.5029	257	0.1436	-	-
0.5049	258	0.0859	-	-
0.5068	259	0.2157	-	-
0.5088	260	0.1455	0.1029	0.9058
0.5108	261	0.1974	-	-
0.5127	262	0.1667	-	-
0.5147	263	0.1512	-	-
0.5166	264	0.1684	-	-
0.5186	265	0.2132	0.1012	0.9053
0.5205	266	0.1645	-	-
0.5225	267	0.203	-	-
0.5245	268	0.1539	-	-
0.5264	269	0.1445	-	-
0.5284	270	0.1377	0.0994	0.9056
0.5303	271	0.1719	-	-
0.5323	272	0.1896	-	-
0.5342	273	0.1452	-	-
0.5362	274	0.1275	-	-
0.5382	275	0.1883	0.0980	0.9057
0.5401	276	0.1462	-	-
0.5421	277	0.1595	-	-
0.5440	278	0.1693	-	-
0.5460	279	0.1929	-	-
0.5479	280	0.154	0.0970	0.9053
0.5499	281	0.1468	-	-
0.5519	282	0.0898	-	-
0.5538	283	0.1425	-	-
0.5558	284	0.1362	-	-
0.5577	285	0.1025	0.0978	0.9053
0.5597	286	0.1578	-	-
0.5616	287	0.1235	-	-
0.5636	288	0.1109	-	-
0.5656	289	0.0746	-	-
0.5675	290	0.1471	0.0992	0.9053
0.5695	291	0.2631	-	-
0.5714	292	0.11	-	-
0.5734	293	0.1834	-	-
0.5753	294	0.1277	-	-
0.5773	295	0.2104	0.0990	0.9042
0.5793	296	0.1294	-	-
0.5812	297	0.1672	-	-
0.5832	298	0.2171	-	-
0.5851	299	0.1451	-	-
0.5871	300	0.0871	0.0980	0.9033
0.5890	301	0.0897	-	-
0.5910	302	0.1296	-	-
0.5930	303	0.1206	-	-
0.5949	304	0.1665	-	-
0.5969	305	0.1511	0.0979	0.9032
0.5988	306	0.1566	-	-
0.6008	307	0.1339	-	-
0.6027	308	0.1474	-	-
0.6047	309	0.1022	-	-

Framework Versions

• Python: 3.10.14
• Sentence Transformers: 3.0.1
• Transformers: 4.44.0
• PyTorch: 2.4.0
• Accelerate: 0.33.0
• Datasets: 2.21.0
• 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",
}