SentenceTransformer based on BAAI/bge-base-en
This is a sentence-transformers model finetuned from BAAI/bge-base-en on the json 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: BAAI/bge-base-en
- Maximum Sequence Length: 512 tokens
- Output Dimensionality: 768 dimensions
- Similarity Function: Cosine Similarity
- Training Dataset:
- json
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': 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("RK-1235/bge-base-FIR-matryoshka-BASELINE-10epo-triplet")
# Run inference
sentences = [
'Under which section of the law was Rahul Shishupal apprehended?',
'raw liquor near the temple in the forest. The informant then left. We hid our two motorcycles and approached the person stealthily. When we reached the person, we noticed a large crowd around him. Seeing us, the crowd dispersed. We apprehended the person selling liquor with a show of force. After questioning the apprehended individual about his name and address and conducting a search, he identified himself as Rahul Shishupal, aged approximately 28 years, from Nanakganj Jhala village, Kotwali Police Station, Hardeo. During the search, a plastic bottle containing approximately 10 liters of raw liquor was seized. Opening the lid of the bottle, we smelled a pungent odor of raw liquor. The act of the apprehended individual falls under Section 60 ex.act. The accused was informed of his offense under Section 60 ex.act. When asked for authorization documents regarding the possession and sale of illegal raw liquor, he was unable to produce them and requested forgiveness for his mistake. The',
'Mann son Saudan residing Kanhor Thana Pahadi Bharatpur Rajasthan, 5. Mustak son Hariya residing Ghagwadi Thana Kathwada Bharatpur Rajasthan, 6. Ikram son Iliaas residing Jamat Thana Punhana Noonu Mevata Haryana, 7. Nasir son Raju residing Bisru Thana Punhana Noonu Mevata Haryana, 8. Sahun son Rahmuddin residing Dhaulpur Thana Dhaulpur Faridabad Haryana, 9. Hakku alias Hakmu alias Hakmuddin son Nasru alias Nasrudeen residing Bichhor Thana Bichhor Noonu Mevata Haryana, 10. Kala alias Kala Minister son Kanura alias Kalua residing Kanhor Thana Pahadi Bharatpur Rajasthan are active members. The main activity of this gang is robbery, looting, and illegal smuggling which involves illegal money making, earning money to support themselves and their families, causing considerable fear and terror in the area. Due to the fear of this gang, no person from the public is willing to give testimony or write reports against them. These are habitual criminals described under Chapter 17 of the IPC. It is',
]
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
- Dataset:
dim_1024
- Evaluated with
InformationRetrievalEvaluator
with these parameters:{ "truncate_dim": 1024 }
Metric | Value |
---|---|
cosine_accuracy@1 | 0.3889 |
cosine_accuracy@3 | 0.6824 |
cosine_accuracy@5 | 0.7301 |
cosine_accuracy@10 | 0.7974 |
cosine_precision@1 | 0.3889 |
cosine_precision@3 | 0.2275 |
cosine_precision@5 | 0.146 |
cosine_precision@10 | 0.0797 |
cosine_recall@1 | 0.3889 |
cosine_recall@3 | 0.6824 |
cosine_recall@5 | 0.7301 |
cosine_recall@10 | 0.7974 |
cosine_ndcg@10 | 0.6082 |
cosine_mrr@10 | 0.5462 |
cosine_map@100 | 0.5512 |
Information Retrieval
- Dataset:
dim_768
- Evaluated with
InformationRetrievalEvaluator
with these parameters:{ "truncate_dim": 768 }
Metric | Value |
---|---|
cosine_accuracy@1 | 0.3889 |
cosine_accuracy@3 | 0.6824 |
cosine_accuracy@5 | 0.7301 |
cosine_accuracy@10 | 0.7974 |
cosine_precision@1 | 0.3889 |
cosine_precision@3 | 0.2275 |
cosine_precision@5 | 0.146 |
cosine_precision@10 | 0.0797 |
cosine_recall@1 | 0.3889 |
cosine_recall@3 | 0.6824 |
cosine_recall@5 | 0.7301 |
cosine_recall@10 | 0.7974 |
cosine_ndcg@10 | 0.6082 |
cosine_mrr@10 | 0.5462 |
cosine_map@100 | 0.5512 |
Information Retrieval
- Dataset:
dim_512
- Evaluated with
InformationRetrievalEvaluator
with these parameters:{ "truncate_dim": 512 }
Metric | Value |
---|---|
cosine_accuracy@1 | 0.3843 |
cosine_accuracy@3 | 0.6719 |
cosine_accuracy@5 | 0.7288 |
cosine_accuracy@10 | 0.7876 |
cosine_precision@1 | 0.3843 |
cosine_precision@3 | 0.224 |
cosine_precision@5 | 0.1458 |
cosine_precision@10 | 0.0788 |
cosine_recall@1 | 0.3843 |
cosine_recall@3 | 0.6719 |
cosine_recall@5 | 0.7288 |
cosine_recall@10 | 0.7876 |
cosine_ndcg@10 | 0.6014 |
cosine_mrr@10 | 0.5402 |
cosine_map@100 | 0.5455 |
Information Retrieval
- Dataset:
dim_256
- Evaluated with
InformationRetrievalEvaluator
with these parameters:{ "truncate_dim": 256 }
Metric | Value |
---|---|
cosine_accuracy@1 | 0.3719 |
cosine_accuracy@3 | 0.6431 |
cosine_accuracy@5 | 0.7026 |
cosine_accuracy@10 | 0.768 |
cosine_precision@1 | 0.3719 |
cosine_precision@3 | 0.2144 |
cosine_precision@5 | 0.1405 |
cosine_precision@10 | 0.0768 |
cosine_recall@1 | 0.3719 |
cosine_recall@3 | 0.6431 |
cosine_recall@5 | 0.7026 |
cosine_recall@10 | 0.768 |
cosine_ndcg@10 | 0.5814 |
cosine_mrr@10 | 0.5204 |
cosine_map@100 | 0.5256 |
Information Retrieval
- Dataset:
dim_128
- Evaluated with
InformationRetrievalEvaluator
with these parameters:{ "truncate_dim": 128 }
Metric | Value |
---|---|
cosine_accuracy@1 | 0.3366 |
cosine_accuracy@3 | 0.5915 |
cosine_accuracy@5 | 0.6601 |
cosine_accuracy@10 | 0.717 |
cosine_precision@1 | 0.3366 |
cosine_precision@3 | 0.1972 |
cosine_precision@5 | 0.132 |
cosine_precision@10 | 0.0717 |
cosine_recall@1 | 0.3366 |
cosine_recall@3 | 0.5915 |
cosine_recall@5 | 0.6601 |
cosine_recall@10 | 0.717 |
cosine_ndcg@10 | 0.5366 |
cosine_mrr@10 | 0.4778 |
cosine_map@100 | 0.4843 |
Information Retrieval
- Dataset:
dim_64
- Evaluated with
InformationRetrievalEvaluator
with these parameters:{ "truncate_dim": 64 }
Metric | Value |
---|---|
cosine_accuracy@1 | 0.2719 |
cosine_accuracy@3 | 0.485 |
cosine_accuracy@5 | 0.5497 |
cosine_accuracy@10 | 0.6209 |
cosine_precision@1 | 0.2719 |
cosine_precision@3 | 0.1617 |
cosine_precision@5 | 0.1099 |
cosine_precision@10 | 0.0621 |
cosine_recall@1 | 0.2719 |
cosine_recall@3 | 0.485 |
cosine_recall@5 | 0.5497 |
cosine_recall@10 | 0.6209 |
cosine_ndcg@10 | 0.4495 |
cosine_mrr@10 | 0.3944 |
cosine_map@100 | 0.4024 |
Training Details
Training Dataset
json
- Dataset: json
- Size: 801 training samples
- Columns:
anchor
,positive
, andnegative
- Approximate statistics based on the first 801 samples:
anchor positive negative type string string list details - min: 9 tokens
- mean: 19.53 tokens
- max: 41 tokens
- min: 16 tokens
- mean: 197.47 tokens
- max: 410 tokens
- size: 5 elements
- Samples:
anchor positive negative What were the clothing details of the person identified by the special informant near the storage shed?
was ready to come forward as a witness. Out of necessity, we police officials searched each other to ensure none of us had any incriminating items. Subsequently, accompanied by the special informant, we proceeded to the location indicated. Upon reaching the storage shed near the crematorium ghat, the special informant pointed out a person wearing black and slate-colored jersey and jeans standing behind the wall of the storage shed. We police officials parked our motorcycles nearby, hid ourselves, and approached the back wall where the person was standing. Seeing us, the individual started running, and we police officials caught him after using necessary force. The arrested person's name and address were asked, and he stated his name as Shahvez son of Mowlai No.Mo., Kakra Khurd Thana Kotwali, Shahjahanpur, age approximately 25 years. A search of his person revealed a homemade indigenous firearm 315 bore hidden in the left pocket of his pants, with a total length of one ballist three
['Bablu alias Umesh Kumar Kushwaha, son of Nathoo Prasad Kushwaha, residing in Gram Pachokhar, Than Ahra, Bandha, was conducted. Opening the white plastic bag held in his right hand revealed marijuana. The weight was measured using an electronic scale borrowed from Constable Vijay Singh in the town of Attara, which showed the weight of the marijuana to be 1 kilogram 500 grams. When asked for a license to keep and sell it, he could not show it. The act of Bablu alias Umesh Kumar Kushwaha as mentioned above constitutes a punishable offense under Section 8/20 NDPS Act. Being informed of the offense, he was taken into custody at the Gram Garganpurawa police station from the Garganpurawa turnoff, about 20 steps from Garganpurawa on the river embankment road. The seized marijuana without license of 1 kilogram 500 grams was taken into police custody. A sample of 50 grams was separated from the seized marijuana, and the remaining 1.45 kilograms of marijuana and 50 grams of sample were kept', 'First Information Report: A DCM vehicle numbered UP19T5287 loaded with large animal bones and two accused under Sections 420/278 IPC, Kotwali police station, Basti district, today on the date 01.09.23, while Inspector Rajendra Yadav was touring the area with officers Akhilesh Yadav and Indrajit Paswan, along with employees of Hamaraa Chitra 18, reached near the Toll Plaza Basti when a DCM vehicle numbered UP19T5287 passed by from Gorakhpur, emitting a strong foul smell. Due to the vehicle slowing down near the toll plaza, the driver was signaled to stop on the left side of the road. The names and addresses of the driver and the person sitting with him were asked. The driver introduced himself as Mintu Kumar, son of Tellu Ram, residing in Aldi Police Station, Shamli district, age 3 NC RB (N.C.R.B) I.L.F.-I (Unified Investigation Form - I), 24 years old. The name and address of the person sitting with the driver were also asked, who introduced himself as Deshpal SIO Krishnapal, residing', '(Unified Investigation Form -1), Purva Case, Tikra Village, Asandra Police Station, Barabanki District. A search of his person revealed a plastic bottle filled with liquid substance in his right hand. Opening the cap of the bottle, we smelled a strong odor of raw liquor. When asked for a license to carry liquor, he refused to show it and requested forgiveness for his mistake. The above-mentioned person was taken into custody under Section 60(1) of the Act around 6:05 PM. During the arrest, strict adherence was given to the orders and directives of the Human Rights Commission and the Honorable Supreme Court. The bottle cap was resealed, and witnesses were sought from the public without revealing their names. The seized bottle was brought to the police station and sealed with a serial number seal. Notice of arrest will be given to the relative. The statement will be written, read, and heard before being signed by the concerned parties. Premchand Rawat, signature HC. Ali Ahmad, signature', 'police post. Upon questioning the arrested person for name and address, 3 NC R.B (N.C.R.B) I.L.F.-I (Unified Investigation Form - I) was filled, and a body search was conducted. The arrested person stated his name as Sanjay Rajput, son of Ramasare, residing in Jhinjhak Vasti Ward No. 5 Durgais Nagar Police Station Mangalpur District Dehat Kanipalwar, age approximately 35 years. During the body search, 15 units of country liquor were seized from the right hand held plastic bag. When questioned about the illegal country liquor, he stated that he buys liquor from contractors and sells it village to village for more money. When asked for a license to sell, he failed to show one and started asking for forgiveness for the mistake. The act of the arrested person falls under the ambit of Section 60 Excise Act. The arrested person was informed of the charge under Section 60 EXACT.KS and was arrested around 10:22 PM. The illegal country liquor was seized by the police. At the time of arrest,', 'First Information Report: Oral Statement - It was stated that I am SHO Sanjeev Kumar Dubey, there are 20 numbered cartridges with Dal 1443 Dalveer Singh, one each; 20 numbered cartridges with 1504 Sandeep Kumar, one each; driving a government jeep UP 85 AG 0415. Departed from Jayprakash on the day of the incident Imroz, stopped for investigation and check and ATM and the suspect vehicle and search desired criminals and investigation gang chart approved by Shri District Magistrate Mathura, Gang Leader 1. Amir Khan son Rahmat Khan residing Akeda Thana Sadar Noonu Mevata Haryana was informed that people reported in various places that Amir Khan residing Akeda Thana Sadar Noonu Mevata Haryana is part of an organized group, its members are 2. Muslim alias Hakimi son Masood alias Sunder Jamat Thana Punhana Noonu Mevata Haryana, 3. Ajriddin alias Ajru alias Ajju son Azad residing Ghagwadi Thana Kathwada Bharatpur Rajasthan, 4. Manish alias Mann son Saudan residing Kanhor Thana Pahadi']
How did the police officials manage to catch the individual after he started running?
was ready to come forward as a witness. Out of necessity, we police officials searched each other to ensure none of us had any incriminating items. Subsequently, accompanied by the special informant, we proceeded to the location indicated. Upon reaching the storage shed near the crematorium ghat, the special informant pointed out a person wearing black and slate-colored jersey and jeans standing behind the wall of the storage shed. We police officials parked our motorcycles nearby, hid ourselves, and approached the back wall where the person was standing. Seeing us, the individual started running, and we police officials caught him after using necessary force. The arrested person's name and address were asked, and he stated his name as Shahvez son of Mowlai No.Mo., Kakra Khurd Thana Kotwali, Shahjahanpur, age approximately 25 years. A search of his person revealed a homemade indigenous firearm 315 bore hidden in the left pocket of his pants, with a total length of one ballist three
['hid behind motorcycles and approached stealthily, arresting the individual named Sunil, son of Harishchandra, residing in Rudapurwa Majra, Nayagaon, Mubarakpur, Kotwali Police Station, Dehat Hardoi, approximately 36 years old. A search of his person revealed a plastic container with about 14 liters of liquid. Upon questioning, he admitted it was raw alcohol. Opening the container lid, a strong smell of raw alcohol was detected. When asked for a license to sell and possess raw alcohol, he refused to show one and requested forgiveness for his mistake. His actions constituted an offense under Section 60 ExAct. He was informed of the charges and taken into custody at 7:25 PM. The seized container was prepared with a memo, sealed, and stamped. During the arrest, orders and guidelines from the Supreme Court and National Commission were strictly followed. Some people came during the arrest but left without giving their names or addresses after being asked for witness statements. This report', 'First Information Report: This is a handwritten complaint submitted in the Hindi service, addressed to Shri Inspector Sir, Thana Motipur, Bahraich district, Sir, it is stated that the complainant Poonam, wife of Ramabhilakh, residing in Jayarampurwa, Kudwaa, Thana Motipur, Bahraich, am living there. On the date 11.01.2024, at 4 PM, Dr. Urff Ramesh, son of Bala Lodhi, residing in Kaalapurwa, Mo Nagar, Thana Ramgaon, Bahraich district, took away my daughter Nisha, aged about 14 years, daughter of Ramabhilakh. Today, my daughter told me that Dr. Urff Ramesh forcibly took her away. Due to which I have come to the police station with my daughter. Therefore, I request Mr. Sir to kindly write my case and take appropriate action against the accused. Ref No. Poonam 3 N.C.R.B (N.C.R.B) I.L.F.-1 (Unified Investigation Form -1) Complainant Poonam, wife of Ramabhilakh, Village Jayarampurwa, Kudwaa, Thana Motipur, Bahraich, Mobile No. 7052270342 Date 17.01 2024 The registration of the case was done', 'Barabanki, approximately 23 years old. From his body search, a total of 1120 rupees was recovered, including two 500 rupee notes, two 50 rupee notes, and one 20 rupee note. The second individual identified himself as Muhammad Imran, son of Shahid Ali, residing in Dhakauli Thana, Kotwali Nagar district, Barabanki, approximately 25 years old. From his body search, a total of 1030 rupees was recovered, including two 500 rupee notes, one 20 rupee note, and one 10 rupee note. The third individual identified himself as Radhe, son of Sohki Lal, residing in Dhakauli Thana, Kotwali Nagar district, Barabanki, approximately 19 years old. From his body search, a total of 720 rupees was recovered, including one 500 rupee note, two 100 rupee notes, and one 20 rupee note. The fourth individual identified himself as Sanjay, son of Kanaku, residing in Dhakauli Thana, Kotwali Nagar district, Barabanki, approximately 20 years old. From his body search, a total of 750 rupees was recovered, including one', "neck and cheeks with the intention of killing her, which put the petitioner in a critical condition and blood started flowing from her neck. He also attacked Munni Devi, a neighbor of the petitioner. Then Munni Devi started shouting loudly, so he ran downstairs with the knife. Some people downstairs caught him and called the police by dialing 112. Then the police took him to the concerned police station, and the petitioner's treatment is ongoing at Motilal Nehru Medical College where her condition has become serious. The opponent is aggressive and violent and wants to kill the petitioner. If a case is not registered against him under severe sections, an accident can happen to the petitioner at any time. The opponent is a criminal type of person from before, and his brother is also supporting him. Therefore, respectfully requested to Mr. Sir that kindly register a case against the opponent for attempted murder and kindly register the case under severe sections and kindly register the", '(First Information Report): A fake case report of 10 liters of raw liquor and arrest of one person under Section 60 of the Excise Act today on the date 22/3/24 by me, Shivraj Singh, UNI, May, UNI Shivraj Singh May, UNI Shaitan Singh HC 231 Sanjay Kumar from Haja Police Station with report No. 06 at time 1:06 PM was on duty for verification and checking of individuals, vehicles, and investigation in the area. When we reached near Samaspur Gate, we saw a sudden panic when a person holding a plastic bottle suddenly ran away quickly upon seeing us, which made us suspicious. We chased him and caught him near Samaspur Gate about 20 steps away at around 3:00 PM. Upon questioning the arrested individual, his name was Thakur Das, son of Thakur Singh RIO, police station Chatari, Vikroori, district Bulandshahr, age approximately 40 years. He was holding a white plastic can of about 10 liters in his right hand. Opening the lid of the plastic can, we smelled the odor of raw liquor. When asked for a']
What specific details were provided about the homemade indigenous firearm found on the arrested person?
pants, with a total length of one ballist three inches, barrel iron approximately eight inches, stock iron approximately four inches, and hammer iron approximately four inches, with wooden plates screwed on both sides, trigger hammer operational, and a pin with a cap to open and close the barrel with a spring. Additionally, a live cartridge 315 bore was found in his right pocket, with 8 mm KF written on its base. The arrested person complained of pain in the lower abdomen, stating it was due to an injury from falling in the morning. When asked for a license for the firearm and cartridge, Shahvez son of Mowlai could not show it and requested forgiveness for his mistake. Since his act falls under Section 3/25 A. Act, which is a punishable offense, the NAFKAL took him into custody at 12:40 PM, citing the reason. The seized firearm and cartridge were kept in a cloth bag, sealed, and stamped with a sample seal. Arrest and seizure memos were prepared. During the arrest and seizure, the
['attached with screws. The hammer is made of iron, the total length being 2 cm (1 inch). The trigger guard is made of iron with a screw for opening and closing attached to an iron plate on the other side. The seized firearm is a brass cartridge marked KFSMM on its base. This act falls under the chargeable offense under Section 3/25 A Act. At around 10:10 am, while informing about the arrest, the orders and guidelines of the Human Rights Commission and the Supreme Court were followed, and Himanshu Singh son of Veerendra Singh, residing in Paradhan, Kotwali town, Maun district, was taken into custody under Section 3/25 A Act. One motorcycle vehicle numbered UPS4 AB7344 was seized from the scene, and when asked for registration, he could not show any, which is an offense under 207 M.V. Act. A report has been filed under 207 MV Act. The seized illegal firearm and cartridge were placed in a transparent plastic box brought by Constable Ka0 Manu Kumar and sealed with a sample seal. The case', "under Section 4/25 AACT. Therefore, the accused Jitendra Pal was informed of his crime under Section 4/25 AACT and was taken into custody at 23:15 hours at the police station. The seized sword was also taken into custody, wrapped in white cloth, sealed, and a sample seal was prepared. Requests for witness statements were made to those present, but due to various reasons, everyone left without giving their names and addresses. During the arrest and seizure, strict adherence to the orders and instructions of the Supreme Court and the Human Rights Commission was maintained. The accused's arrest was informed to his family members, and the FIR was written by talking to the local residents, including Ankrit Gupta, and read out to them. Handwritten notes in Hindi and English are illegible. The notes were attested by Balveer Singh PNO 062250708 and typed by Sonu on the computer.", "and began pleading for forgiveness. At around 19:15, the apprehended individual was taken into custody under Section 60(1) of the Excise Act. A sample of 01 liter was extracted from the plastic container for examination and placed in a plastic bottle. The container and bottle were sealed with a white cloth and stamped as evidence. An arrest memo was prepared on the spot. During the seizure and arrest, strict adherence to the orders and guidelines of the Supreme Court and the Human Rights Commission was maintained. Due to the urgency of the situation, no public witness was present. The report was written and read out loud by Vivek Kumar in sufficient light from a mobile phone and torch, and all concerned parties were informed. The arrested individual's family will be notified through appropriate means upon arrival at the police station. Note: A copy of the report was given to the accused on the spot but was destroyed. Note: Copy of the original report - H.M. Ajit Kumar
- Loss:
MultipleNegativesRankingLoss
with these parameters:{ "scale": 20.0, "similarity_fct": "cos_sim" }
Training Hyperparameters
Non-Default Hyperparameters
eval_strategy
: epochper_device_train_batch_size
: 32per_device_eval_batch_size
: 16gradient_accumulation_steps
: 8learning_rate
: 2e-05num_train_epochs
: 50lr_scheduler_type
: cosinewarmup_ratio
: 0.1bf16
: Truetf32
: Trueload_best_model_at_end
: Trueoptim
: adamw_torch_fusedbatch_sampler
: no_duplicates
All Hyperparameters
Click to expand
overwrite_output_dir
: Falsedo_predict
: Falseeval_strategy
: epochprediction_loss_only
: Trueper_device_train_batch_size
: 32per_device_eval_batch_size
: 16per_gpu_train_batch_size
: Noneper_gpu_eval_batch_size
: Nonegradient_accumulation_steps
: 8eval_accumulation_steps
: Nonetorch_empty_cache_steps
: Nonelearning_rate
: 2e-05weight_decay
: 0.0adam_beta1
: 0.9adam_beta2
: 0.999adam_epsilon
: 1e-08max_grad_norm
: 1.0num_train_epochs
: 50max_steps
: -1lr_scheduler_type
: cosinelr_scheduler_kwargs
: {}warmup_ratio
: 0.1warmup_steps
: 0log_level
: passivelog_level_replica
: warninglog_on_each_node
: Truelogging_nan_inf_filter
: Truesave_safetensors
: Truesave_on_each_node
: Falsesave_only_model
: Falserestore_callback_states_from_checkpoint
: Falseno_cuda
: Falseuse_cpu
: Falseuse_mps_device
: Falseseed
: 42data_seed
: Nonejit_mode_eval
: Falseuse_ipex
: Falsebf16
: Truefp16
: Falsefp16_opt_level
: O1half_precision_backend
: autobf16_full_eval
: Falsefp16_full_eval
: Falsetf32
: Truelocal_rank
: 0ddp_backend
: Nonetpu_num_cores
: Nonetpu_metrics_debug
: Falsedebug
: []dataloader_drop_last
: Falsedataloader_num_workers
: 0dataloader_prefetch_factor
: Nonepast_index
: -1disable_tqdm
: Falseremove_unused_columns
: Truelabel_names
: Noneload_best_model_at_end
: Trueignore_data_skip
: Falsefsdp
: []fsdp_min_num_params
: 0fsdp_config
: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}fsdp_transformer_layer_cls_to_wrap
: Noneaccelerator_config
: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}deepspeed
: Nonelabel_smoothing_factor
: 0.0optim
: adamw_torch_fusedoptim_args
: Noneadafactor
: Falsegroup_by_length
: Falselength_column_name
: lengthddp_find_unused_parameters
: Noneddp_bucket_cap_mb
: Noneddp_broadcast_buffers
: Falsedataloader_pin_memory
: Truedataloader_persistent_workers
: Falseskip_memory_metrics
: Trueuse_legacy_prediction_loop
: Falsepush_to_hub
: Falseresume_from_checkpoint
: Nonehub_model_id
: Nonehub_strategy
: every_savehub_private_repo
: Nonehub_always_push
: Falsegradient_checkpointing
: Falsegradient_checkpointing_kwargs
: Noneinclude_inputs_for_metrics
: Falseinclude_for_metrics
: []eval_do_concat_batches
: Truefp16_backend
: autopush_to_hub_model_id
: Nonepush_to_hub_organization
: Nonemp_parameters
:auto_find_batch_size
: Falsefull_determinism
: Falsetorchdynamo
: Noneray_scope
: lastddp_timeout
: 1800torch_compile
: Falsetorch_compile_backend
: Nonetorch_compile_mode
: Noneinclude_tokens_per_second
: Falseinclude_num_input_tokens_seen
: Falseneftune_noise_alpha
: Noneoptim_target_modules
: Nonebatch_eval_metrics
: Falseeval_on_start
: Falseuse_liger_kernel
: Falseeval_use_gather_object
: Falseaverage_tokens_across_devices
: Falseprompts
: Nonebatch_sampler
: no_duplicatesmulti_dataset_batch_sampler
: proportional
Training Logs
Epoch | Step | Training Loss | dim_1024_cosine_ndcg@10 | dim_768_cosine_ndcg@10 | dim_512_cosine_ndcg@10 | dim_256_cosine_ndcg@10 | dim_128_cosine_ndcg@10 | dim_64_cosine_ndcg@10 |
---|---|---|---|---|---|---|---|---|
1.0 | 4 | - | 0.5307 | 0.5307 | 0.5140 | 0.4598 | 0.3836 | 0.2600 |
2.0 | 8 | - | 0.5500 | 0.5500 | 0.5329 | 0.4736 | 0.3953 | 0.2692 |
2.6154 | 10 | 21.2344 | - | - | - | - | - | - |
3.0 | 12 | - | 0.5777 | 0.5777 | 0.5644 | 0.5024 | 0.4182 | 0.2931 |
4.0 | 16 | - | 0.6006 | 0.6006 | 0.5897 | 0.5327 | 0.4507 | 0.3240 |
5.0 | 20 | 15.3903 | 0.6073 | 0.6073 | 0.5992 | 0.5528 | 0.4884 | 0.3596 |
6.0 | 24 | - | 0.5985 | 0.5985 | 0.5978 | 0.5574 | 0.5060 | 0.3928 |
7.0 | 28 | - | 0.5997 | 0.5997 | 0.5919 | 0.5598 | 0.5199 | 0.4097 |
7.6154 | 30 | 11.3886 | - | - | - | - | - | - |
8.0 | 32 | - | 0.5996 | 0.5996 | 0.5934 | 0.5659 | 0.5254 | 0.4136 |
9.0 | 36 | - | 0.6068 | 0.6068 | 0.5969 | 0.5743 | 0.5326 | 0.4163 |
10.0 | 40 | 6.435 | 0.6084 | 0.6084 | 0.6003 | 0.5792 | 0.5376 | 0.4281 |
11.0 | 44 | - | 0.6133 | 0.6133 | 0.6087 | 0.5801 | 0.5446 | 0.4370 |
12.0 | 48 | - | 0.6207 | 0.6207 | 0.6102 | 0.5898 | 0.5459 | 0.4448 |
12.6154 | 50 | 4.2559 | - | - | - | - | - | - |
13.0 | 52 | - | 0.6285 | 0.6285 | 0.6171 | 0.5947 | 0.5488 | 0.4461 |
14.0 | 56 | - | 0.6236 | 0.6236 | 0.6111 | 0.5925 | 0.5483 | 0.4556 |
15.0 | 60 | 2.2983 | 0.6216 | 0.6216 | 0.6144 | 0.5899 | 0.5492 | 0.4556 |
16.0 | 64 | - | 0.6177 | 0.6177 | 0.6116 | 0.5883 | 0.5504 | 0.4552 |
17.0 | 68 | - | 0.6178 | 0.6178 | 0.6095 | 0.5866 | 0.5433 | 0.4508 |
17.6154 | 70 | 1.7678 | - | - | - | - | - | - |
18.0 | 72 | - | 0.6127 | 0.6127 | 0.6030 | 0.5812 | 0.5392 | 0.4491 |
19.0 | 76 | - | 0.6071 | 0.6071 | 0.6018 | 0.5805 | 0.5381 | 0.4479 |
20.0 | 80 | 1.1051 | 0.6082 | 0.6082 | 0.5988 | 0.5781 | 0.5338 | 0.4438 |
21.0 | 84 | - | 0.6085 | 0.6085 | 0.6001 | 0.5788 | 0.5340 | 0.4448 |
22.0 | 88 | - | 0.6119 | 0.6119 | 0.6050 | 0.5826 | 0.5396 | 0.4483 |
22.6154 | 90 | 0.8751 | - | - | - | - | - | - |
23.0 | 92 | - | 0.6143 | 0.6143 | 0.6088 | 0.5858 | 0.5413 | 0.4467 |
24.0 | 96 | - | 0.6156 | 0.6156 | 0.6101 | 0.5886 | 0.5427 | 0.4510 |
25.0 | 100 | 0.6431 | 0.6157 | 0.6157 | 0.6103 | 0.5882 | 0.5464 | 0.4530 |
26.0 | 104 | - | 0.6100 | 0.6100 | 0.6041 | 0.5820 | 0.5407 | 0.4479 |
27.0 | 108 | - | 0.6074 | 0.6074 | 0.6001 | 0.5814 | 0.5377 | 0.4472 |
27.6154 | 110 | 0.6123 | - | - | - | - | - | - |
28.0 | 112 | - | 0.6069 | 0.6069 | 0.6026 | 0.5797 | 0.5362 | 0.4481 |
29.0 | 116 | - | 0.6068 | 0.6068 | 0.6006 | 0.5806 | 0.5355 | 0.4447 |
30.0 | 120 | 0.4621 | 0.6085 | 0.6085 | 0.5993 | 0.5809 | 0.5348 | 0.4441 |
31.0 | 124 | - | 0.6076 | 0.6076 | 0.5980 | 0.5791 | 0.5342 | 0.4464 |
32.0 | 128 | - | 0.6081 | 0.6081 | 0.5946 | 0.5781 | 0.5305 | 0.4424 |
32.6154 | 130 | 0.4917 | - | - | - | - | - | - |
33.0 | 132 | - | 0.6057 | 0.6057 | 0.5966 | 0.5746 | 0.5324 | 0.4436 |
34.0 | 136 | - | 0.6048 | 0.6048 | 0.5939 | 0.5756 | 0.5307 | 0.4458 |
35.0 | 140 | 0.3875 | 0.6059 | 0.6059 | 0.5980 | 0.5776 | 0.5336 | 0.4475 |
36.0 | 144 | - | 0.6061 | 0.6061 | 0.5966 | 0.5763 | 0.5347 | 0.4465 |
37.0 | 148 | - | 0.6079 | 0.6079 | 0.5937 | 0.5761 | 0.5316 | 0.4444 |
37.6154 | 150 | 0.4292 | - | - | - | - | - | - |
38.0 | 152 | - | 0.6063 | 0.6063 | 0.5927 | 0.5752 | 0.5298 | 0.4427 |
39.0 | 156 | - | 0.6078 | 0.6078 | 0.5956 | 0.5756 | 0.5304 | 0.4436 |
40.0 | 160 | 0.3469 | 0.6064 | 0.6064 | 0.5950 | 0.5748 | 0.5314 | 0.4426 |
41.0 | 164 | - | 0.6092 | 0.6092 | 0.5982 | 0.5782 | 0.5305 | 0.4450 |
42.0 | 168 | - | 0.6084 | 0.6084 | 0.5988 | 0.5783 | 0.5330 | 0.4466 |
42.6154 | 170 | 0.3876 | - | - | - | - | - | - |
43.0 | 172 | - | 0.6084 | 0.6084 | 0.6014 | 0.5791 | 0.5360 | 0.4495 |
44.0 | 176 | - | 0.6095 | 0.6095 | 0.6008 | 0.5800 | 0.5379 | 0.4489 |
45.0 | 180 | 0.358 | 0.6102 | 0.6102 | 0.6019 | 0.5809 | 0.5371 | 0.4486 |
46.0 | 184 | - | 0.6098 | 0.6098 | 0.6009 | 0.5783 | 0.5391 | 0.4479 |
47.0 | 188 | - | 0.6083 | 0.6083 | 0.6009 | 0.5794 | 0.5369 | 0.4487 |
47.6154 | 190 | 0.3588 | - | - | - | - | - | - |
48.0 | 192 | - | 0.6087 | 0.6087 | 0.6031 | 0.5799 | 0.5358 | 0.4480 |
49.0 | 196 | - | 0.6100 | 0.6100 | 0.6020 | 0.5802 | 0.5362 | 0.4482 |
50.0 | 200 | 0.2932 | 0.6082 | 0.6082 | 0.6014 | 0.5814 | 0.5366 | 0.4495 |
- The bold row denotes the saved checkpoint.
Framework Versions
- Python: 3.10.12
- Sentence Transformers: 4.1.0
- Transformers: 4.52.2
- PyTorch: 2.6.0+cu124
- Accelerate: 1.7.0
- Datasets: 3.6.0
- Tokenizers: 0.21.1
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",
}
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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Model tree for RK-1235/bge-base-FIR-matryoshka-BASELINE-10epo-triplet
Base model
BAAI/bge-base-enEvaluation results
- Cosine Accuracy@1 on dim 1024self-reported0.389
- Cosine Accuracy@3 on dim 1024self-reported0.682
- Cosine Accuracy@5 on dim 1024self-reported0.730
- Cosine Accuracy@10 on dim 1024self-reported0.797
- Cosine Precision@1 on dim 1024self-reported0.389
- Cosine Precision@3 on dim 1024self-reported0.227
- Cosine Precision@5 on dim 1024self-reported0.146
- Cosine Precision@10 on dim 1024self-reported0.080
- Cosine Recall@1 on dim 1024self-reported0.389
- Cosine Recall@3 on dim 1024self-reported0.682