Views
No views yet
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()
)pip install -U sentence-transformers1from sentence_transformers import SentenceTransformer
2
3# Download from the 🤗 Hub
4model = SentenceTransformer("sabber/worksphere-regulations-embedding_bge")
5# Run inference
6sentences = [
7 "How can I ensure that the curing compound we receive at the job site meets the required specifications with the manufacturer's original containers and labels intact?",
8 "8. Curing:\n03 00 00\nCONCRETE AND CONCRETE REINFORCING\nPage 10 of 18\n6) Curing compound to be delivered to the job site in the manufacturer's original containers only, with original label containing the following:\na) Manufacturer's name\nb) Trade name of the material\nc) Batch number or symbol with which test samples may be correlated",
9 '2. For Large Wind Energy Systems:\na. The minimum acreage for a large wind system shall be established based on the setbacks of the turbine(s) and the height of the turbine(s);\nb. All turbines located within the same large wind system property shall be of a similar tower design, including the type, number of blades, and direction of blade rotation;\nc. Large wind systems shall be setback at least one and one-half times the height of the turbine and rotor diameter from the property line. Large wind systems shall also be setback at least one and one-half times the height of the turbine from above ground telephone, electrical lines, and other uninhabitable structures;\nd. Towers shall not be climbable up to 15 feet above ground level.',
10]
11embeddings = model.encode(sentences)
12print(embeddings.shape)
13# [3, 768]
14
15# Get the similarity scores for the embeddings
16similarities = model.similarity(embeddings, embeddings)
17print(similarities.shape)
18# [3, 3]dim_1024, dim_768, dim_512 and dim_256InformationRetrievalEvaluator| Metric | dim_1024 | dim_768 | dim_512 | dim_256 |
|---|---|---|---|---|
| cosine_accuracy@1 | 0.0307 | 0.0307 | 0.03 | 0.0295 |
| cosine_accuracy@3 | 0.3986 | 0.3986 | 0.3907 | 0.3774 |
| cosine_accuracy@5 | 0.5774 | 0.5774 | 0.5644 | 0.5502 |
| cosine_accuracy@10 | 0.7881 | 0.7881 | 0.7819 | 0.7644 |
| cosine_precision@1 | 0.0307 | 0.0307 | 0.03 | 0.0295 |
| cosine_precision@3 | 0.1329 | 0.1329 | 0.1302 | 0.1258 |
| cosine_precision@5 | 0.1155 | 0.1155 | 0.1129 | 0.11 |
| cosine_precision@10 | 0.0788 | 0.0788 | 0.0782 | 0.0764 |
| cosine_recall@1 | 0.0307 | 0.0307 | 0.03 | 0.0295 |
| cosine_recall@3 | 0.3986 | 0.3986 | 0.3907 | 0.3774 |
| cosine_recall@5 | 0.5774 | 0.5774 | 0.5644 | 0.5502 |
| cosine_recall@10 | 0.7881 | 0.7881 | 0.7819 | 0.7644 |
| cosine_ndcg@1 | 0.0307 | 0.0307 | 0.03 | 0.0295 |
| cosine_ndcg@3 | 0.2318 | 0.2318 | 0.2266 | 0.2191 |
| cosine_ndcg@5 | 0.3041 | 0.3041 | 0.2968 | 0.2887 |
| cosine_ndcg@10 | 0.3753 | 0.3753 | 0.3706 | 0.3613 |
| cosine_mrr@1 | 0.0307 | 0.0307 | 0.03 | 0.0295 |
| cosine_mrr@3 | 0.1752 | 0.1752 | 0.171 | 0.1654 |
| cosine_mrr@5 | 0.2144 | 0.2144 | 0.2091 | 0.2031 |
| cosine_mrr@10 | 0.2457 | 0.2457 | 0.2416 | 0.235 |
| cosine_map@100 | 0.2551 | 0.2551 | 0.2512 | 0.2453 |
question and context| question | context | |
|---|---|---|
| type | string | string |
| details |
|
|
| question | context |
|---|---|
Are there any specific guidelines or requirements for the installation of tree supports as outlined in the regulations? | SECTION 32 93 00:[object Object]Cast-in-Place 31 25 14 - Erosion and 32 13 13 - Concrete Paving. 32 13 16 - Decorative Concrete. a. Measurement 1) Measured per each Tree planted. b. Payment 1) The work performed and materials and measured as provided under price bid per each for Tree 2) Various caliper inches. The price bid shall include: 1) Furnishing and installing Tree as 2) Preparing excavation pit 3) Topsoil, fertilizer, mulch, and planting mix, 1 = . , 1 = Tree. , 1 = furnished in accordance with this item "Measurement" will be paid for at the unit for:. planted, 1 = . specified, 1 = . by the Drawings, 1 = . supports, 1 = . [Insert Bid Number], 1 = . [Insert, 1 = . 4), 1 = Plant. Number], 1 = Number]. Engineering Project, 1 = Engineering Project[object Object]Effective July 1, 2024[object Object]32 93 00[object Object]PLANTINGS[object Object]Page 2 of 24[object Object]eee[object Object]BER[object Object]BPRERR |
What specific information do I need to include in my application to meet the standards for grouted installations? | 1.1 SUMMARY:[object Object]= . 36, 2 = . 36, 3 = (1) requirements a qualified testing laboratory.. 37, 1 = . 37, 2 = . 37, 3 = Submit a minimum of 3 other similar projects where the proposed grout mix. 38, 1 = . 38, 2 = . 38, 3 = design was used.. 39 40, 1 = . 39 40, 2 = . 39 40, 3 = anticipated volumes of grout to be pumped for each. , 1 = . , 2 = . , 3 = Submit application and reach grouted.. 41, 1 = 4.. 41, 2 = . 41, 3 = Additional requirements for installations of carrier pipe 24-inch and larger:. 42, 1 = . 42, 2 = a.. 42, 3 = Submit work plan describing the carrier pipe installation equipment, materials. 43 44, 1 = . 43 44, 2 = b.. 43 44, 3 = employed. For installations without holding jacks or a restrained spacer, provide buoyant[object Object]CITY OF DENTON STANDARD CONSTRUCTION SPECIFICATION DOCUMENTS Revised October 22, 2020 Effective July 1, 2024[object Object][Insert Engineering Project Number] [Insert Bid Number][object Object]eK[object Object]BWN[object Object]nA[object Object]20[object Object]21[object Object]22[object Object]23[object Object]24 |
In the event of a quasi judicial hearing, who else besides the site owner(s) should we inform about the decision notification process, and how do we manage their requests for a copy of the decision? | Notice of Decision:[object Object]1. Within 10 days after a final decision on an application, the Director shall provide written notification of the decision, unless the applicant was present at the meeting where the decision was made or required by law.[object Object]2. If the review involves a quasi-judicial hearing, the Director shall, within 10 days after a final decision on the application, provide a written notification of the decision to the owner(s) of the subject site (unless the applicant was present at the meeting where the decision was made or required by law), and any other person that submitted a written request for a copy of the decision before its effective date. |
MatryoshkaLoss with these parameters:
1{
2 "loss": "MultipleNegativesRankingLoss",
3 "matryoshka_dims": [
4 768,
5 512,
6 256
7 ],
8 "matryoshka_weights": [
9 1,
10 1,
11 1
12 ],
13 "n_dims_per_step": -1
14}eval_strategy: epochper_device_train_batch_size: 32per_device_eval_batch_size: 16gradient_accumulation_steps: 16learning_rate: 2e-05num_train_epochs: 8lr_scheduler_type: cosinewarmup_ratio: 0.1bf16: Truetf32: Trueload_best_model_at_end: Trueoptim: adamw_torch_fusedbatch_sampler: no_duplicatesoverwrite_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: 16eval_accumulation_steps: Nonelearning_rate: 2e-05weight_decay: 0.0adam_beta1: 0.9adam_beta2: 0.999adam_epsilon: 1e-08max_grad_norm: 1.0num_train_epochs: 8max_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: Falsehub_always_push: Falsegradient_checkpointing: Falsegradient_checkpointing_kwargs: Noneinclude_inputs_for_metrics: Falseeval_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: Nonedispatch_batches: Nonesplit_batches: Noneinclude_tokens_per_second: Falseinclude_num_input_tokens_seen: Falseneftune_noise_alpha: Noneoptim_target_modules: Nonebatch_eval_metrics: Falseprompts: Nonebatch_sampler: no_duplicatesmulti_dataset_batch_sampler: proportional| Epoch | Step | Training Loss | dim_1024_cosine_ndcg@10 | dim_768_cosine_ndcg@10 | dim_512_cosine_ndcg@10 | dim_256_cosine_ndcg@10 |
|---|---|---|---|---|---|---|
| 0.2974 | 10 | 2.3168 | - | - | - | - |
| 0.5948 | 20 | 1.2839 | - | - | - | - |
| 0.8922 | 30 | 0.6758 | - | - | - | - |
| 0.9814 | 33 | - | 0.3592 | 0.3592 | 0.3556 | 0.3496 |
| 1.1896 | 40 | 0.4651 | - | - | - | - |
| 1.4870 | 50 | 0.3707 | - | - | - | - |
| 1.7844 | 60 | 0.2941 | - | - | - | - |
| 1.9926 | 67 | - | 0.3732 | 0.3732 | 0.3699 | 0.3601 |
| 2.0818 | 70 | 0.2651 | - | - | - | - |
| 2.3792 | 80 | 0.2341 | - | - | - | - |
| 2.6766 | 90 | 0.2093 | - | - | - | - |
| 2.9740 | 100 | 0.1812 | 0.3747 | 0.3747 | 0.3718 | 0.3626 |
| 3.2714 | 110 | 0.1717 | - | - | - | - |
| 3.5688 | 120 | 0.1496 | - | - | - | - |
| 3.8662 | 130 | 0.1472 | - | - | - | - |
| 3.9851 | 134 | - | 0.3742 | 0.3742 | 0.3727 | 0.3628 |
| 4.1636 | 140 | 0.1304 | - | - | - | - |
| 4.4610 | 150 | 0.1229 | - | - | - | - |
| 4.7584 | 160 | 0.1085 | - | - | - | - |
| 4.9963 | 168 | - | 0.3745 | 0.3745 | 0.3717 | 0.361 |
| 5.0558 | 170 | 0.1144 | - | - | - | - |
| 5.3532 | 180 | 0.1088 | - | - | - | - |
| 5.6506 | 190 | 0.0937 | - | - | - | - |
| 5.9480 | 200 | 0.1023 | - | - | - | - |
| 5.9777 | 201 | - | 0.3749 | 0.3749 | 0.3704 | 0.3603 |
| 6.2454 | 210 | 0.0942 | - | - | - | - |
| 6.5428 | 220 | 0.0919 | - | - | - | - |
| 6.8401 | 230 | 0.0939 | - | - | - | - |
| 6.9888 | 235 | - | 0.3755 | 0.3755 | 0.3705 | 0.3603 |
| 7.1375 | 240 | 0.0925 | - | - | - | - |
| 7.4349 | 250 | 0.0928 | - | - | - | - |
| 7.7323 | 260 | 0.0869 | - | - | - | - |
| 7.8513 | 264 | - | 0.3753 | 0.3753 | 0.3706 | 0.3613 |
1@inproceedings{reimers-2019-sentence-bert,
2 title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
3 author = "Reimers, Nils and Gurevych, Iryna",
4 booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
5 month = "11",
6 year = "2019",
7 publisher = "Association for Computational Linguistics",
8 url = "https://arxiv.org/abs/1908.10084",
9}1@misc{kusupati2024matryoshka,
2 title={Matryoshka Representation Learning},
3 author={Aditya Kusupati and Gantavya Bhatt and Aniket Rege and Matthew Wallingford and Aditya Sinha and Vivek Ramanujan and William Howard-Snyder and Kaifeng Chen and Sham Kakade and Prateek Jain and Ali Farhadi},
4 year={2024},
5 eprint={2205.13147},
6 archivePrefix={arXiv},
7 primaryClass={cs.LG}
8}1@misc{henderson2017efficient,
2 title={Efficient Natural Language Response Suggestion for Smart Reply},
3 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},
4 year={2017},
5 eprint={1705.00652},
6 archivePrefix={arXiv},
7 primaryClass={cs.CL}
8}