metadata

tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:2000
  - loss:CoSENTLoss
base_model: avsolatorio/GIST-small-Embedding-v0
widget:
  - source_sentence: do vivid seats tickets work?
    sentences:
      - >-
        Charlotte-Mecklenburg Schools will be closed for students on Friday due
        to the forecast of severe weather. ... CMS staff members work with city
        and county leaders to receive the most up-to-date information about road
        and weather conditions.
      - >-
        Tickets are $40 per ticket and $400 for a table of ten. Tickets are
        available for purchase when you register for the show.
      - >-
        This service is currently offered free of charge by the bank. You can
        get the last 'Available' balance of your account (by an SMS) by giving a
        Missed Call to 18008431122. You can get the Mini Statement (by an SMS)
        for last 5 transactions in your account by giving a Missed Call to
        18008431133. 1.
  - source_sentence: is alexa compatible with tv?
    sentences:
      - >-
        To fix this Echo red light, start with the restart of the router and
        Amazon Echo. In case, the restart process doesn't work, check for the
        device and app update in Alexa app. If it's available, click the
        'Update' button for compatibility reason.
      - >-
        Ligament - A small band of dense, white, fibrous elastic tissue.
        Ligaments connect the ends of bones together in order to form a joint.
        Tendon - A tough, flexible band of fibrous connective tissue that
        connects muscles to bones.
      - >-
        There are 610 calories in a 1 bowl serving of El Pollo Loco Original
        Pollo Bowl.
  - source_sentence: can you play fortnite save the world on mac?
    sentences:
      - >-
        ['In the Music app on your Mac, click iTunes Store in the sidebar. ...
        ', 'Click Purchased (below Quick Links) near the top right of the iTunes
        Store window.', 'Click Music near the top right of the page that
        appears. ... ', 'To download an item, click its Download button .']
      - >-
        Essential Oils in the Second and Third Trimesters. "In the second and
        third trimesters, some essential oils are safe to use, as your baby is
        more developed," Edwards adds. These include lavender, chamomile, and
        ylang ylang—all of which calm, relax, and aid sleep.
      - >-
        ADR holders do not have to transact the trade in the foreign currency or
        worry about exchanging currency on the forex market. ... ADRs list on
        either the New York Stock Exchange (NYSE), American Stock Exchange
        (AMEX), or the Nasdaq, but they are also sold over-the-counter (OTC).
  - source_sentence: how long does money take to transfer boi?
    sentences:
      - >-
        When will it take more than one working day? It will take more than one
        working day to reach your payee's bank when: You make a payment online
        after 3.30pm in the Republic of Ireland or after 4.30pm in Northern
        Ireland and Great Britain on a working day. Your payment will begin to
        process on the next working day.
      - >-
        If you had bought just one share of Microsoft at the IPO, you would now
        have 288 shares after all the splits. Those shares would be worth
        $44,505 at the current stock quote of $154.53. A $5,000 investment would
        have purchased 238 shares at the IPO price.
      - >-
        FKM is the American standard ASTM short form name for Fluro-Elastomer.
        ... VITON™ is a registered trademark of Du Pont performance elastomers,
        the original developers of the rubber. However, the Viton is also used
        as a general name for the material, no matter who the manufacturer is.
  - source_sentence: how long is a texas vehicle inspection report good for?
    sentences:
      - >-
        ['Aerospace engineer.', 'Automotive engineer.', 'CAD technician.',
        'Contracting civil engineer.', 'Control and instrumentation engineer.',
        'Maintenance engineer.', 'Mechanical engineer.', 'Nuclear engineer.']
      - >-
        A key difference is that it's simpler to unlock a credit lock than it is
        to “thaw” a credit freeze. But a freeze may afford legal protections
        that a lock doesn't. ... The credit bureaus sometimes promote their
        credit lock services, which can carry a monthly fee, alongside their
        credit freeze options, which are free.
      - >-
        If your car fails its MOT you can only continue to drive it if the
        previous year's MOT is still valid - which might occur if you submitted
        the car for its test two weeks early. You can still drive it away from
        the testing centre or garage if no 'dangerous' problems were identified
        during the MOT.
pipeline_tag: sentence-similarity
library_name: sentence-transformers

SentenceTransformer based on avsolatorio/GIST-small-Embedding-v0

This is a sentence-transformers model finetuned from avsolatorio/GIST-small-Embedding-v0. 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: avsolatorio/GIST-small-Embedding-v0
Maximum Sequence Length: 512 tokens
Output Dimensionality: 384 dimensions
Similarity Function: Cosine Similarity

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': 384, '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("moshew/gist_small_ft_gooaq_v3")
# Run inference
sentences = [
    'how long is a texas vehicle inspection report good for?',
    "If your car fails its MOT you can only continue to drive it if the previous year's MOT is still valid - which might occur if you submitted the car for its test two weeks early. You can still drive it away from the testing centre or garage if no 'dangerous' problems were identified during the MOT.",
    "['Aerospace engineer.', 'Automotive engineer.', 'CAD technician.', 'Contracting civil engineer.', 'Control and instrumentation engineer.', 'Maintenance engineer.', 'Mechanical engineer.', 'Nuclear engineer.']",
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 384]

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

Training Details

Training Dataset

Unnamed Dataset

Size: 2,000 training samples
Columns: sentence1, sentence2, and label
Approximate statistics based on the first 1000 samples:
sentence1 sentence2 label
type string string float
details
min: 8 tokens
mean: 12.05 tokens
max: 23 tokens

min: 13 tokens
mean: 59.84 tokens
max: 124 tokens

min: 0.0
mean: 0.5
max: 1.0

	sentence1	sentence2	label
type	string	string	float
details	min: 8 tokens mean: 12.05 tokens max: 23 tokens	min: 13 tokens mean: 59.84 tokens max: 124 tokens	min: 0.0 mean: 0.5 max: 1.0

Samples:

sentence1	sentence2	label
`what is the difference between rapid rise yeast and bread machine yeast?`	`Though there are some minor differences in shape and nutrients, Rapid-Rise Yeast is (pretty much) the same as Instant Yeast and Bread Machine Yeast. ... Also, Rapid-Rise Yeast is a little more potent than Active Dry Yeast and can be mixed in with your dry ingredients directly.`	`1.0`
`what is the difference between rapid rise yeast and bread machine yeast?`	`Fermentation recycles NAD+, and produces 2 ATPs. In lactic acid fermentation, pyruvate from glycolysis changes to lactic acid. ... In alcoholic fermentation, pyruvate changes to alcohol and carbon dioxide. This type of fermentation is carried out by yeasts and some bacteria.`	`0.0`
`are light kits universal for ceiling fans?`	`Not all Universal Light Kits are actually Universal. They can be universal to only that manufacturer. ... Casablanca and Hunter Ceiling Fan Light Kits are universal only to their own fans.`	`1.0`

Loss: CoSENTLoss with these parameters:

{
    "scale": 20.0,
    "similarity_fct": "pairwise_cos_sim"
}

Training Hyperparameters

Non-Default Hyperparameters

per_device_train_batch_size: 16
per_device_eval_batch_size: 16
num_train_epochs: 1
warmup_ratio: 0.1
seed: 12
bf16: True
dataloader_num_workers: 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: 16
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: 1.0
num_train_epochs: 1
max_steps: -1
lr_scheduler_type: linear
lr_scheduler_kwargs: {}
warmup_ratio: 0.1
warmup_steps: 0
log_level: passive
log_level_replica: warning
log_on_each_node: True
logging_nan_inf_filter: True
save_safetensors: True
save_on_each_node: False
save_only_model: False
restore_callback_states_from_checkpoint: False
no_cuda: False
use_cpu: False
use_mps_device: False
seed: 12
data_seed: None
jit_mode_eval: False
use_ipex: False
bf16: True
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: 4
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}
tp_size: 0
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
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: proportional

Training Logs

Epoch	Step	Training Loss
0.008	1	3.5339

Framework Versions

Python: 3.11.12
Sentence Transformers: 4.1.0
Transformers: 4.51.3
PyTorch: 2.6.0+cu124
Accelerate: 1.5.2
Datasets: 3.5.0
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",
}

CoSENTLoss

@online{kexuefm-8847,
    title={CoSENT: A more efficient sentence vector scheme than Sentence-BERT},
    author={Su Jianlin},
    year={2022},
    month={Jan},
    url={https://kexue.fm/archives/8847},
}