Instructions to use Trelis/multi-qa-MiniLM-L6-dot-v1-ft-pairs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Trelis/multi-qa-MiniLM-L6-dot-v1-ft-pairs with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("Trelis/multi-qa-MiniLM-L6-dot-v1-ft-pairs")

sentences = [
"What is the minimum force that players of both defending and attacking teams should use when making a touch?",
"touch football australia 2020 11 13. 5. 5 when possession changes after the half is touched or when the half places the ball on or over the try line ; or 13. 5. 6 in replacement of a penalty tap ; or 13. 5. 7 when so directed by the referee. 13. 6 a player is to perform a rollball seven ( 7 ) metres in - field under the following circumstances : 13. 6. 1 when a change of possession takes place due to a player in possession making contact with the sideline or any ground outside the field of play, prior to a touch being made ; or 13. 6. 2 when the ball not in possession of a player makes contact with the sideline or any ground outside the field of play. 13. 7 a player may not perform a tap in replacement of a rollball. ruling = the offending team must return to the mark and perform the rollball. 13. 8 an attacking player, other than the player performing the rollball, may receive the ball at the rollball and shall do so without delay. that player is referred to as the half. 13. 9 the half may control the ball with a foot prior to picking up the ball. 13. 10 a player",
"or passed and goes to ground during play, a change of possession results. ruling = the mark for the change of possession is where the ball makes initial contact with the ground. 9. 5 if the ball, while still under the control of the half, contacts the ground in the in - goal area, possession is lost. ruling = play will restart with a rollball at the nearest point on the seven ( 7 ) metre line. fit playing rules - 5th edition 8 copyright © touch football australia 2020 9. 6 if a player mishandles the ball and even if in an effort to gain control, the ball is accidentally knocked forward into any other player, a change of possession results. 10 the touch 10. 1 a touch may be made by either a defending player or a player in possession. 10. 2 a defending player may not claim a touch if contact has not been made. if a player claims a touch has been made, but the referee is unsure the touch will count. ruling = a penalty to the attacking team at the point of the infringement and the offending player sent to the sin bin. 10. 3 players of both defending and attacking teams are to use the minimum force necessary to make a touch. players must ensure that the",
"is normally forty - five minutes, inclusive of a five ( 5 ) minute half time. end of play when the referee indicates completion of the match. exclusion when a player is sent to the nearest sin bin area following three ( 3 ) penalties by the defending team upon entering their seven metre zone. the player is counted as a player on the field of play and cannot be replaced or interchanged. fit playing rules - 5th edition copyright © touch football australia 2020 1 fit federation of international touch field of play the playing area bounded by the sidelines and dead ball lines, both of which are out of bounds. see appendix 1. forced interchange when a player is required to undertake a compulsory interchange for an infringement ruled more serious than a penalty but less serious than a permanent interchange, sin bin or dismissal. forward a position or direction towards the dead ball line beyond the team ’ s attacking try line. full time the expiration of the second period of time allowed for play. half the player who takes possession following a rollball. half time the break in play between the two halves of a match. imminent about to occur, it is almost certain to occur. infringement the action of a player contrary to the rules of the game. in - goal area the area"
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

Notebooks
Google Colab
Kaggle

SentenceTransformer based on sentence-transformers/multi-qa-MiniLM-L6-dot-v1

This is a sentence-transformers model finetuned from sentence-transformers/multi-qa-MiniLM-L6-dot-v1. 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/multi-qa-MiniLM-L6-dot-v1
Maximum Sequence Length: 512 tokens
Output Dimensionality: 384 tokens
Similarity Function: Dot Product

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: 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})
)

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("Trelis/multi-qa-MiniLM-L6-dot-v1-ft-pairs")
# Run inference
sentences = [
    'What is the ruling if a player in possession holds or impedes a defending player?',
    'directly forward of the point of the infringement. 15. 5 after effecting the touch, the defending player must retire the required seven ( 7 ) metres or to the defending try line as indicated by the referee without interfering with the attacking team. ruling = a penalty to the attacking team ten ( 10 ) metres forward of the infringement or if on the defensive try line, on the seven ( 7 ) metre line. fit playing rules - 5th edition copyright © touch football australia 2020 13 16 obstruction 16. 1 a player in possession must not run or otherwise move behind other attacking players or the referee in an attempt to avoid an imminent touch. ruling = a penalty to the non - offending team at the point of the infringement. 16. 2 the player in possession is not to hold or otherwise impede a defending player in any way. ruling = a penalty to the non - offending team at the point of the infringement. 16. 3 an attacking player in support of the player in possession may move as necessary to achieve a supporting position but must not grab, hold, push or otherwise deliberately interfere with a defending player attempting to make a touch ruling = a penalty to the non - offending team at the point of the infringement or on the seven ( 7',
    '. attacking team the team which has or is gaining possession. behind a position or direction towards a team ’ s defending try line. change of possession the act of moving control of the ball from one team to the other. dead / dead ball when the ball is out of play including the period following a try and until the match is recommenced and when the ball goes to ground and / or outside the boundaries of the field of play prior to the subsequent rollball. dead ball line the end boundaries of the field of play. there is one at each end of the field of play. see appendix 1. defending try line the line which a team has to defend to prevent a try. defending team the team without or which is losing possession. dismissal when a player is sent from the field of play for the rest of the match. drop - off a procedure used to determine a winner following equal scores at the expiration of normal duration. duration the length of time a competition match lasts, which is normally forty - five minutes, inclusive of a five ( 5 ) minute half time. end of play when the referee indicates completion of the match. exclusion when a player is sent to the nearest sin bin area following three ( 3 ) penalties by the',
]
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 Hyperparameters

Non-Default Hyperparameters

eval_strategy: steps
per_device_train_batch_size: 16
per_device_eval_batch_size: 16
learning_rate: 0.0001
num_train_epochs: 1
lr_scheduler_type: constant
warmup_ratio: 0.3

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: steps
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
learning_rate: 0.0001
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: constant
lr_scheduler_kwargs: {}
warmup_ratio: 0.3
warmup_steps: 0
log_level: passive
log_level_replica: warning
log_on_each_node: True
logging_nan_inf_filter: True
save_safetensors: True
save_on_each_node: False
save_only_model: False
restore_callback_states_from_checkpoint: False
no_cuda: False
use_cpu: False
use_mps_device: False
seed: 42
data_seed: None
jit_mode_eval: False
use_ipex: False
bf16: False
fp16: False
fp16_opt_level: O1
half_precision_backend: auto
bf16_full_eval: False
fp16_full_eval: False
tf32: None
local_rank: 0
ddp_backend: None
tpu_num_cores: None
tpu_metrics_debug: False
debug: []
dataloader_drop_last: False
dataloader_num_workers: 0
dataloader_prefetch_factor: None
past_index: -1
disable_tqdm: False
remove_unused_columns: True
label_names: None
load_best_model_at_end: False
ignore_data_skip: False
fsdp: []
fsdp_min_num_params: 0
fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
fsdp_transformer_layer_cls_to_wrap: None
accelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
deepspeed: None
label_smoothing_factor: 0.0
optim: adamw_torch
optim_args: None
adafactor: False
group_by_length: False
length_column_name: length
ddp_find_unused_parameters: None
ddp_bucket_cap_mb: None
ddp_broadcast_buffers: False
dataloader_pin_memory: True
dataloader_persistent_workers: False
skip_memory_metrics: True
use_legacy_prediction_loop: False
push_to_hub: False
resume_from_checkpoint: None
hub_model_id: None
hub_strategy: every_save
hub_private_repo: 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
batch_sampler: batch_sampler
multi_dataset_batch_sampler: proportional

Training Logs

Epoch	Step	Training Loss	loss
0.1667	2	1.5903	1.1222
0.3333	4	1.3817	1.1956
0.5	6	0.8451	1.1244
0.6667	8	1.4958	1.1055
0.8333	10	1.3135	1.0260
1.0	12	1.7283	0.9734

Framework Versions

Python: 3.10.12
Sentence Transformers: 3.0.1
Transformers: 4.42.3
PyTorch: 2.1.1+cu121
Accelerate: 0.31.0
Datasets: 2.17.1
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",
}

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}
}