README.md

metadata

tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - dense
  - generated_from_trainer
  - dataset_size:637
  - loss:TripletLoss
base_model: sentence-transformers/all-MiniLM-L6-v2
widget:
  - source_sentence: >-
      We are the data controller in respect of your personal data and will
      handle your data in accordance with 

      our obligations under the Privacy Laws. We will use this information
      solely in connection with 

      administering the Championship and exploiting the rights  granted to us
      pursuant to any separate 

      agreement entered into with your team or otherwise. We are entitled to do
      so on the basis of our 

      legitimate interests, namely to enable us to operate the Championship and
      promote and exploit your 

      participation in the same.
    sentences:
      - >-
        The aerodynamic design of the new F1 car's rear wing has been optimized
        to reduce drag and improve downforce, allowing drivers to reach higher
        speeds on the straights.
      - >-
        As the data controller, we will manage your personal information in
        accordance with privacy laws, using it solely to administer the Formula
        1 Championship and promote your participation.
      - >-
        The engine's ability to produce power is directly related to the
        pressure of the fuel-air mixture it receives. As the pressure increases,
        so does the potential for power output, with atmospheric pressure
        serving as the maximum threshold for normally aspirated engines.
  - source_sentence: |-
      With adjustments 
      for temperature, altitude, and other factors, the EPR gauge 
      presents an indication of the thrust being developed by 
      the engine. Since the EPR gauge compares two pressures, 
      it is a differential pressure gauge. It is a remote-sensing 
      instrument that receives its input from an engine pressure 
      ratio transmitter or, in digital instrument systems displays, 
      from a computer.
    sentences:
      - >-
        The engine's fuel efficiency can be significantly improved by
        implementing advanced materials in the engine's components.
      - >-
        Prior to the start of the race, all personnel except drivers, officials,
        and technical staff must vacate the grid within 10 minutes. At the
        5-minute signal, all cars on the grid and in the pit lane must have
        their wheels fitted, and tyre blankets disconnected from power supply.
        Team personnel and equipment trolleys must begin leaving the grid at
        this time.
      - >-
        The EPR gauge on an engine provides a reading of the thrust being
        produced by adjusting for various factors such as temperature and
        altitude, and it does this by comparing two different pressures, making
        it a type of differential pressure gauge that receives its input from a
        remote-sensing instrument.
  - source_sentence: >-
      57.5 Unless asked to do so by the FIA, cars may not be moved from the fast
      lane whilst the sprint 

      session or the race is suspended. Any driver whose car is moved from the
      fast lane to any other 

      part of the pit lane  will be arranged at the back of the line of cars in
      the fast lane in the order 

      they got there. At all times drivers must follow the directions of the
      marshals.
    sentences:
      - >-
        The aerodynamic design of F1 cars has led to significant advancements in
        downforce, allowing drivers to take corners at higher speeds and
        improving overall racing performance.
      - >-
        A detailed record of repair work, including photographs and part
        numbers, must be maintained. Additionally, gears, dog rings, and reverse
        components can be changed under supervision during a competition if they
        are damaged, but significant parts of a car's RNC cannot be replaced
        between competitions without FIA permission.
      - >-
        During a suspended sprint session or race, F1 cars are not to be moved
        from the fast lane unless instructed by the FIA. If a driver's car is
        moved to a different part of the pit lane, they will be placed at the
        back of the fast lane in the order they arrived. Marshals' instructions
        must be followed at all times.
  - source_sentence: >-
      If such conditions are not met, then the 

      Power Unit Manufacturer may, at its sole and exclusive discretion, decline
      the request to supply 

      such New Customer Team and the decline of such request shall not be deemed
      to be a breach 

      of the terms set out in this Appendix (however Article c) cannot be
      applied or interpreted by the 

      Power Unit Manufacturer in a way which would d eprive the obligation of
      supply as referred to 

      in Article b) above of any effect and/or that would prevent the FIA from
      making and enforcing 

      the provisions set out in Article b) above. The Power Unit Manufacturer
      undertakes to exercise 

      in good faith the co nditions referred to in paragraph 1 to 11 below). The
      teams and the Power 

      Unit Manufacturers remain free to negotiate the terms of the supply
      agreement, subject to the 

      fall-back positions set out below which shall apply should a team and a
      Power Unit Manufacturer 

      fail to reach an agreement, despite negotiating in good faith.
    sentences:
      - >-
        The clerk of the course has the authority to temporarily halt practice
        sessions to ensure the track is clear or to assist in the recovery of a
        vehicle. During qualifying or sprint qualifying sessions, the session
        duration may be extended as a result of interruptions. Any disputes
        regarding the impact of these interruptions on driver qualification will
        not be accepted.
      - >-
        If a new customer team fails to meet the required conditions, the power
        unit manufacturer has the right to decline their supply request.
        However, this decision cannot be used to circumvent the obligation to
        supply as stated in the agreement. Both parties must negotiate in good
        faith, and if they fail to reach an agreement, the terms set out below
        will apply.
      - >-
        The aerodynamic design of the new generation of F1 cars has led to a
        significant increase in downforce, but at the cost of reduced fuel
        efficiency and increased tire wear.
  - source_sentence: >-
      10.7 Information to be provided to the FIA and Competitors 

      a) In order that an FIA observer may be appointed, Competitors must inform
      the FIA and all 

      other Competitors of any planned TPC, PE or DE at least 72 hours before it
      is due to 

      commence, and the following information must be provided: 

      i) The precise specification of the car(s) to be used. ii) The name(s) of
      the driver(s). iii) The type of activity.
    sentences:
      - >-
        Competitors must notify the FIA and other teams at least 72 hours in
        advance of any planned technical testing, physical evaluations, or
        development exercises, providing detailed information about the cars,
        drivers, and nature of the activity.
      - >-
        Pitot tubes can be either covered or uncovered, and modifications to the
        Driver Cooling Scoop, as outlined in Article 3.6.5 of the Technical
        Regulations, are also permitted. Additionally, changes can be made to
        improve the driver's comfort.
      - >-
        The aerodynamic design of a Formula 1 car's rear wing is crucial in
        determining its overall downforce and drag characteristics, requiring a
        delicate balance between speed and stability.
datasets:
  - zacCMU/RAG_FINETUNING_For_Engineering
pipeline_tag: sentence-similarity
library_name: sentence-transformers

SentenceTransformer based on sentence-transformers/all-MiniLM-L6-v2

This is a sentence-transformers model finetuned from sentence-transformers/all-MiniLM-L6-v2 on the rag_finetuning_for_engineering dataset. It maps sentences & paragraphs to a 384-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: sentence-transformers/all-MiniLM-L6-v2
• Maximum Sequence Length: 256 tokens
• Output Dimensionality: 384 dimensions
• Similarity Function: Cosine Similarity
• Training Dataset:
  • rag_finetuning_for_engineering

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': 256, 'do_lower_case': False, 'architecture': 'BertModel'})
  (1): Pooling({'word_embedding_dimension': 384, '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})
  (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("zacCMU/miniLM2-ENG2")
# Run inference
sentences = [
    '10.7 Information to be provided to the FIA and Competitors \na) In order that an FIA observer may be appointed, Competitors must inform the FIA and all \nother Competitors of any planned TPC, PE or DE at least 72 hours before it is due to \ncommence, and the following information must be provided: \ni) The precise specification of the car(s) to be used. ii) The name(s) of the driver(s). iii) The type of activity.',
    'Competitors must notify the FIA and other teams at least 72 hours in advance of any planned technical testing, physical evaluations, or development exercises, providing detailed information about the cars, drivers, and nature of the activity.',
    "The aerodynamic design of a Formula 1 car's rear wing is crucial in determining its overall downforce and drag characteristics, requiring a delicate balance between speed and stability.",
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 384]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities)
# tensor([[ 1.0000, -0.6238,  0.9745],
#         [-0.6238,  1.0000, -0.6029],
#         [ 0.9745, -0.6029,  1.0000]])

Training Details

Training Dataset

rag_finetuning_for_engineering

• Dataset: rag_finetuning_for_engineering at bddb325
• Size: 637 training samples
• Columns: anchor, positive, and negative
• Approximate statistics based on the first 637 samples:

  	anchor	positive	negative
  type	string	string	string
  details	min: 9 tokens mean: 112.88 tokens max: 256 tokens	min: 18 tokens mean: 60.28 tokens max: 176 tokens	min: 15 tokens mean: 35.03 tokens max: 57 tokens

• Samples:

  anchor	positive	negative
  A penalty in accordance with Article 54.3d) will be imposed on any driver who fails to start the race from the pit lane. If any driver needs assistance after the fifteen (15) second signal, he must raise his arm and, when the remainder of the cars able to do so have left the pit lane, marshals will be instructed to push the car into the inner lane. In this case, marshals with yellow flags will stand beside any car concerned to warn drivers behind.	A driver who fails to start the race from the pit lane will incur a penalty. If a driver requires assistance after the 15-second signal, they must signal for help and marshals will then guide their car into the inner lane, warning other drivers with yellow flags.	The aerodynamic design of modern Formula 1 cars requires a delicate balance between downforce and drag to achieve optimal speed on the track.
  If a driver wishes to leave his car before it is weighed , he must ask the Technical Delegate to weigh him in order that this weight may be added to that of the car. e) If a car stops on the circuit during the qualifying session or the sprint qualifying session and the driver leaves the car, he must go to the FIA garage immediately on his return to the pit lane in order for his weight to be established. 35.2 After the sprint session or the race any classified car may be weighed.	To avoid penalties, a driver must ensure their weight is accurately recorded before leaving their car, either by having the Technical Delegate weigh them or by being weighed in the FIA garage after returning to the pit lane. This process is crucial during qualifying sessions, sprint qualifying sessions, and after the sprint session or the race.	The aerodynamic design of a Formula 1 car's rear wing plays a crucial role in generating downforce, but its impact on the overall handling and stability of the vehicle is often overlooked by teams in their pursuit of speed.
  d) When leaving the pits a driver may overtake, or be overtaken by, another car on the track before he reaches the second safety car line. e) When the safety car is returning to the pits it may be overtaken by cars on the track once it has reached the first safety car line. f) Whilst in the pit entry road, pit lane or pit exit road a driver may overtake another car which is also in one of these three areas.	When exiting the pits, a driver is allowed to overtake or be overtaken by another car on the track before reaching the second safety car line. Additionally, the safety car can be overtaken by cars on the track once it has reached the first safety car line, and drivers can also overtake each other while in the pit entry road, pit lane, or pit exit road.	The aerodynamic design of modern Formula 1 cars relies heavily on complex computational fluid dynamics simulations to optimize their downforce and drag characteristics.

• Loss: TripletLoss with these parameters:

  {
      "distance_metric": "TripletDistanceMetric.EUCLIDEAN",
      "triplet_margin": 5
  }
  

Training Hyperparameters

Non-Default Hyperparameters

• per_device_train_batch_size: 16
• learning_rate: 1e-05
• num_train_epochs: 4

All Hyperparameters

Click to expand

• overwrite_output_dir: False
• do_predict: False
• eval_strategy: no
• prediction_loss_only: True
• per_device_train_batch_size: 16
• per_device_eval_batch_size: 8
• per_gpu_train_batch_size: None
• per_gpu_eval_batch_size: None
• gradient_accumulation_steps: 1
• eval_accumulation_steps: None
• torch_empty_cache_steps: None
• learning_rate: 1e-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: 4
• 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
• 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}
• parallelism_config: 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
• project: huggingface
• trackio_space_id: trackio
• 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
• hub_revision: None
• 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
• include_tokens_per_second: False
• include_num_input_tokens_seen: no
• neftune_noise_alpha: None
• optim_target_modules: None
• batch_eval_metrics: False
• eval_on_start: False
• use_liger_kernel: False
• liger_kernel_config: None
• eval_use_gather_object: False
• average_tokens_across_devices: True
• prompts: None
• batch_sampler: batch_sampler
• multi_dataset_batch_sampler: proportional
• router_mapping: {}
• learning_rate_mapping: {}

Training Logs

Epoch	Step	Training Loss
0.25	10	5.5019
0.5	20	5.2724
0.75	30	5.1275
1.0	40	4.999
1.25	50	4.8488
1.5	60	4.7919
1.75	70	4.6734
2.0	80	4.4696
2.25	90	4.4078
2.5	100	4.2232
2.75	110	4.1736
3.0	120	4.0837
3.25	130	4.0113
3.5	140	4.0376
3.75	150	3.9134
4.0	160	3.9853

Framework Versions

• Python: 3.12.12
• Sentence Transformers: 5.1.2
• Transformers: 4.57.1
• PyTorch: 2.9.0+cu126
• Accelerate: 1.11.0
• Datasets: 4.0.0
• Tokenizers: 0.22.1

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",
}

TripletLoss

@misc{hermans2017defense,
    title={In Defense of the Triplet Loss for Person Re-Identification},
    author={Alexander Hermans and Lucas Beyer and Bastian Leibe},
    year={2017},
    eprint={1703.07737},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}