File size: 66,386 Bytes
fd8a076 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 |
---
base_model: bobox/DeBERTa-small-ST-v1-test-step3
datasets: []
language: []
library_name: sentence-transformers
metrics:
- pearson_cosine
- spearman_cosine
- pearson_manhattan
- spearman_manhattan
- pearson_euclidean
- spearman_euclidean
- pearson_dot
- spearman_dot
- pearson_max
- spearman_max
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:163205
- loss:CachedGISTEmbedLoss
widget:
- source_sentence: interview question on why you want to leave your current job?
sentences:
- Carrier proteins bind and carry the molecules across the cell membrane. These
proteins bind a molecule on one side of the membrane, change shape as they carry
the molecule across the membrane, and deposit the molecule on the other side of
the membrane. Even though a protein is involved in both these methods of transport,
neither method requires energy. Therefore these are still types of passive transport.
- '[''Desire to learn.'', ''Desire to take on more responsibility.'', ''Desire to
take on less responsibility.'', ''Desire to relocate.'', ''Desire for a career
change.'', ''Desire to gain a new skill or grow a current skill.'', ''Company
reorganization has led to change in job content.'']'
- The small intestine is a narrow tube that starts at the stomach and ends at the
large intestine. In adults, it’s about 7 meters (23 feet) long. Most chemical
digestion and almost all nutrient absorption take place in the small intestine.
- source_sentence: 'They say a number of people from the Mujahideen-e-Khalq (MEK)
group were injured at Camp Liberty in Baghdad.
Baghdad has in the past repeatedly denied attacking the group.
MEK members fought with Iraq against Iran in the 1980s, but have since fallen
out with the current Iraqi government.
In an emailed message, the Paris-based National Council of Resistance of Iran
(NCRI), the MEK''s parent group, said dozens of missiles hit the camp on Thursday
evening.
It said two residents were killed and a third later died in hospital of his wounds.
The US condemned the attack "in the strongest terms" and urged Iraq to better
protect the camp.
An Iranian-backed Shia militia, al-Mukhtar Army, said it had fired rockets at
the camp, Reuters news agency reported.
The camp is located in a former US military base, near Baghdad''s airport.
The Iraqi authorities have made no public comments on the report. However, one
security official was quoted by the Associated Press as saying four rockets hit
the camp, injuring two people.
In September, the MEK accused Iraqi forces of attacking Camp Ashraf north-east
of Baghdad and killing 52 of the group''s members.
In recent years, Baghdad has been trying to dismantle MEK camps and eject the
group.
Iran considers the MEK a terrorist group.
The group was removed from the US state department''s list of terrorist organisations
last year.'
sentences:
- A rocket attack has killed three members of an Iranian opposition group in Iraq,
the group and its parent organisation say.
- Directions See How It's Made. 1 Preheat the oven to 375 degrees. 2 Heat a large
skillet over medium heat. 3 Add the spinach. Spread the spinach mixture evenly
on the bottom of the prepared baking 1 dish. Bake until the egg whites are set,
about 25 minutes. Let the casserole sit for about 5 minutes, and then cut into
pieces and 1 serve. Submit a Correction.
- 'Toll free phone number: 011-44-871-246-0002. Ryan Airlines www.ryanair.com is
a low-fare airlines headquartered in Dublin, Ireland. Transporting over 103 million
passengers last year there are 1600 daily flights with 185 destinations. The Ryan
fleet consists of 300 new Boeing 737-800 aircraft in operation with 283 738 aircraft
on order.'
- source_sentence: In what unit is heat measured in?
sentences:
- The heat that is either absorbed or released is measured in joules. The mass is
measured in grams. The change in temperature is given by , where is the final
temperature and is the initial temperature.
- The nitrogen atom of a primary amine is bonded to two hydrogen atoms and one carbon.
The nitrogen atom of a secondary amine is bonded to one hydrogen and two carbons.
The nitrogen atom of a tertiary amine is bonded to three carbon atoms. Amines
are typically named by a common system rather than by IUPAC guidelines. The common
system for naming amines along with several examples is shown below.
- 'Seattle Symphony Live @ Benaroya Hall — Windborne''s The Music of David Bowie:
A Rock Symphony with the Seattle Symphony Tuesday, 10 January, 2017 7:30PM Join
conductor Brent Havens and a full rock band on a symphonic musical odyssey that
explores the incredible range of David Bowie’s Music.'
- source_sentence: meristematic tissue definition
sentences:
- In this chapter, you saw how pressure and buoyancy of fluids can be used to make
work easier — from raising a car on a lift to floating a ship on the ocean. Devices
that make work easier are called machines in physics.
- A Land Rover is splashing water as it crosses a river.
- "meristem. n. 1. (Botany) a plant tissue responsible for growth, whose cells divide\
\ and differentiate to form the tissues and organs of the plant. Meristems occur\
\ within the stem (see cambium) and leaves and at the tips of stems and roots.\
\ [C19: from Greek meristos divided, from merizein to divide, from meris portion].\
\ (Ë\x88mÉ\x9Br É\x99Ë\x8CstÉ\x9Bm)."
- source_sentence: More than 190 countries and territories around the world had confirmed
coronavirus cases by March 22 , 2020 .
sentences:
- when electricity flows to a light bulb , the light bulb will come on
- As of 22 March , more than 337,000 cases of COVID-19 have been reported in over
190 countries and territories , resulting in more than 14,400 deaths and 96,000
recoveries .
- a greenhouse is used to protect plants by keeping them warm
model-index:
- name: SentenceTransformer based on bobox/DeBERTa-small-ST-v1-test-step3
results:
- task:
type: semantic-similarity
name: Semantic Similarity
dataset:
name: sts test
type: sts-test
metrics:
- type: pearson_cosine
value: 0.8778303207829065
name: Pearson Cosine
- type: spearman_cosine
value: 0.9030437588441012
name: Spearman Cosine
- type: pearson_manhattan
value: 0.9058577790072662
name: Pearson Manhattan
- type: spearman_manhattan
value: 0.9024990017391836
name: Spearman Manhattan
- type: pearson_euclidean
value: 0.9066522007596656
name: Pearson Euclidean
- type: spearman_euclidean
value: 0.9032262992393169
name: Spearman Euclidean
- type: pearson_dot
value: 0.8593106541530915
name: Pearson Dot
- type: spearman_dot
value: 0.865145302860828
name: Spearman Dot
- type: pearson_max
value: 0.9066522007596656
name: Pearson Max
- type: spearman_max
value: 0.9032262992393169
name: Spearman Max
---
# SentenceTransformer based on bobox/DeBERTa-small-ST-v1-test-step3
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [bobox/DeBERTa-small-ST-v1-test-step3](https://huggingface.co/bobox/DeBERTa-small-ST-v1-test-step3) on the bobox/enhanced_nli-50_k 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:** [bobox/DeBERTa-small-ST-v1-test-step3](https://huggingface.co/bobox/DeBERTa-small-ST-v1-test-step3) <!-- at revision df9aaa75fe0c2791e5ed35ff33de1689d9a5f5ff -->
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 768 tokens
- **Similarity Function:** Cosine Similarity
- **Training Dataset:**
- bobox/enhanced_nli-50_k
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->
### Model Sources
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
### Full Model Architecture
```
SentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: DebertaV2Model
(1): Pooling({'word_embedding_dimension': 768, '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})
)
```
## Usage
### Direct Usage (Sentence Transformers)
First install the Sentence Transformers library:
```bash
pip install -U sentence-transformers
```
Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer
# Download from the 🤗 Hub
model = SentenceTransformer("bobox/DeBERTa-small-ST-v1-test-UnifiedDatasets-Ft-checkpoints-tmp")
# Run inference
sentences = [
'More than 190 countries and territories around the world had confirmed coronavirus cases by March 22 , 2020 .',
'As of 22 March , more than 337,000 cases of COVID-19 have been reported in over 190 countries and territories , resulting in more than 14,400 deaths and 96,000 recoveries .',
'a greenhouse is used to protect plants by keeping them warm',
]
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]
```
<!--
### Direct Usage (Transformers)
<details><summary>Click to see the direct usage in Transformers</summary>
</details>
-->
<!--
### Downstream Usage (Sentence Transformers)
You can finetune this model on your own dataset.
<details><summary>Click to expand</summary>
</details>
-->
<!--
### Out-of-Scope Use
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
-->
## Evaluation
### Metrics
#### Semantic Similarity
* Dataset: `sts-test`
* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
| Metric | Value |
|:--------------------|:----------|
| pearson_cosine | 0.8778 |
| **spearman_cosine** | **0.903** |
| pearson_manhattan | 0.9059 |
| spearman_manhattan | 0.9025 |
| pearson_euclidean | 0.9067 |
| spearman_euclidean | 0.9032 |
| pearson_dot | 0.8593 |
| spearman_dot | 0.8651 |
| pearson_max | 0.9067 |
| spearman_max | 0.9032 |
<!--
## Bias, Risks and Limitations
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
-->
<!--
### Recommendations
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
-->
## Training Details
### Training Dataset
#### bobox/enhanced_nli-50_k
* Dataset: bobox/enhanced_nli-50_k
* Size: 163,205 training samples
* Columns: <code>sentence1</code> and <code>sentence2</code>
* Approximate statistics based on the first 1000 samples:
| | sentence1 | sentence2 |
|:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
| type | string | string |
| details | <ul><li>min: 4 tokens</li><li>mean: 36.63 tokens</li><li>max: 370 tokens</li></ul> | <ul><li>min: 2 tokens</li><li>mean: 54.93 tokens</li><li>max: 363 tokens</li></ul> |
* Samples:
| sentence1 | sentence2 |
|:----------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| <code>apple customer number</code> | <code>Apple Customer Service. 800-676-2775. Before dialing Apple Customer Service. We've tried for years to eliminate that 44 minute wait for you. But the fact is that it can still take many phone calls to Apple to resolve your issue. Now you can hire GetHuman to do all the work on the phone for you.</code> |
| <code>Molly 's Game grossed more than $ 28.5 million in the US and Canada and less than $ 24.65 in other countries .</code> | <code>, Molly 's Game has grossed $ 28.8 million in the United States and Canada , and $ 24.6 million in other territories , for a worldwide total of $ 53.4 million .</code> |
| <code>mawk definition</code> | <code>Definitions for mawk. Here are all the possible meanings and translations of the word mawk. Wiktionary(0.00 / 0 votes)Rate this definition: Origin: From mawk, mauk, a contraction of mathek, from maðkr, a diminutive of a base from maþa- (Old English maþa), from Indo-European *math-, moth- used in reference to insects and vermin. Cognate with Danish madike, Swedish mask, archaic English maddock (modern maggot).</code> |
* Loss: [<code>CachedGISTEmbedLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters:
```json
{'guide': SentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) 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()
), 'temperature': 0.025}
```
### Evaluation Dataset
#### bobox/enhanced_nli-50_k
* Dataset: bobox/enhanced_nli-50_k
* Size: 3,052 evaluation samples
* Columns: <code>sentence1</code> and <code>sentence2</code>
* Approximate statistics based on the first 1000 samples:
| | sentence1 | sentence2 |
|:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
| type | string | string |
| details | <ul><li>min: 4 tokens</li><li>mean: 33.13 tokens</li><li>max: 313 tokens</li></ul> | <ul><li>min: 2 tokens</li><li>mean: 58.53 tokens</li><li>max: 422 tokens</li></ul> |
* Samples:
| sentence1 | sentence2 |
|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| <code>Dwight Beare, 27, from Melbourne, Australia, was killed in the crash near to the 16th milestone on the TT course on the Isle of Man.<br>Mr Beare suffered fatal spine and back injuries on the west of the island on 4 June at about 14:10 BST.<br>A verdict of misadventure was recorded by Coroner John Needham at Douglas Court House earlier.<br>Mr Needham said: "I am not in a position to give an exact reason for the loss of control but Mr Beare would have died almost instantaneously".<br>The inquest heard from a witness who said the carpenter and his passenger, Benjamin Binns, were thrown into the air after their vehicle hit the road side.<br>Mr Binns, who was airlifted to hospital with a broken leg, said before the race both he and Mr Beare had been "excited and confident".<br>"I will miss my friend dearly and his memory will live on," he said.<br>No defects were found on the vehicle.<br>Mr Beare moved to Onchan on the Isle of Man to pursue his road racing passion.<br>He made his TT debut in 2014 finishing 12th in the second race of the week, with his father Noel as his passenger.<br>He returned in 2015 when he came 17th.</code> | <code>A TT racer died after being thrown from his sidecar when he hit the side of a road, an inquest has heard.</code> |
| <code>are yeezy adidas or nike?</code> | <code>Adidas Yeezy is a fashion collaboration between the German sportswear brand Adidas and American designer Kanye West. The collaboration has become notable for its high-end sneakers, and the Yeezy Boost sneaker line has been considered one of the most influential sneaker brands in the world.</code> |
| <code>what remains are changed into natural gas by heat and pressure change?</code> | <code>heat and pressure change the remains of prehistoric living things into natural gas. Dinosaurs and Other Prehistoric Creatures Dinosaurs are just one group of prehistoric animals. <br> heat and pressure change the remains of dinosaurs into natural gas</code> |
* Loss: [<code>CachedGISTEmbedLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters:
```json
{'guide': SentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) 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()
), 'temperature': 0.025}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `eval_strategy`: steps
- `per_device_train_batch_size`: 320
- `per_device_eval_batch_size`: 128
- `learning_rate`: 2e-05
- `weight_decay`: 0.0001
- `num_train_epochs`: 2
- `lr_scheduler_type`: cosine_with_restarts
- `lr_scheduler_kwargs`: {'num_cycles': 3}
- `warmup_ratio`: 0.25
- `save_safetensors`: False
- `fp16`: True
- `push_to_hub`: True
- `hub_model_id`: bobox/DeBERTa-small-ST-v1-test-UnifiedDatasets-Ft-checkpoints-tmp
- `hub_strategy`: all_checkpoints
- `batch_sampler`: no_duplicates
#### All Hyperparameters
<details><summary>Click to expand</summary>
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: steps
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 320
- `per_device_eval_batch_size`: 128
- `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`: 2e-05
- `weight_decay`: 0.0001
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `max_grad_norm`: 1.0
- `num_train_epochs`: 2
- `max_steps`: -1
- `lr_scheduler_type`: cosine_with_restarts
- `lr_scheduler_kwargs`: {'num_cycles': 3}
- `warmup_ratio`: 0.25
- `warmup_steps`: 0
- `log_level`: passive
- `log_level_replica`: warning
- `log_on_each_node`: True
- `logging_nan_inf_filter`: True
- `save_safetensors`: False
- `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`: True
- `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`: True
- `resume_from_checkpoint`: None
- `hub_model_id`: bobox/DeBERTa-small-ST-v1-test-UnifiedDatasets-Ft-checkpoints-tmp
- `hub_strategy`: all_checkpoints
- `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
- `eval_use_gather_object`: False
- `batch_sampler`: no_duplicates
- `multi_dataset_batch_sampler`: proportional
</details>
### Training Logs
<details><summary>Click to expand</summary>
| Epoch | Step | Training Loss | loss | sts-test_spearman_cosine |
|:------:|:----:|:-------------:|:------:|:------------------------:|
| 0.0020 | 1 | 0.107 | - | - |
| 0.0039 | 2 | 0.1529 | - | - |
| 0.0059 | 3 | 0.1874 | - | - |
| 0.0078 | 4 | 0.1682 | - | - |
| 0.0098 | 5 | 0.1438 | 0.1470 | 0.9078 |
| 0.0117 | 6 | 0.2961 | - | - |
| 0.0137 | 7 | 0.3019 | - | - |
| 0.0157 | 8 | 0.1184 | - | - |
| 0.0176 | 9 | 0.3176 | - | - |
| 0.0196 | 10 | 0.2234 | 0.1468 | 0.9078 |
| 0.0215 | 11 | 0.1881 | - | - |
| 0.0235 | 12 | 0.1593 | - | - |
| 0.0254 | 13 | 0.1833 | - | - |
| 0.0274 | 14 | 0.1352 | - | - |
| 0.0294 | 15 | 0.3143 | 0.1462 | 0.9077 |
| 0.0313 | 16 | 0.1583 | - | - |
| 0.0333 | 17 | 0.2015 | - | - |
| 0.0352 | 18 | 0.1476 | - | - |
| 0.0372 | 19 | 0.1676 | - | - |
| 0.0391 | 20 | 0.1525 | 0.1454 | 0.9079 |
| 0.0411 | 21 | 0.1717 | - | - |
| 0.0431 | 22 | 0.198 | - | - |
| 0.0450 | 23 | 0.3062 | - | - |
| 0.0470 | 24 | 0.1241 | - | - |
| 0.0489 | 25 | 0.1087 | 0.1446 | 0.9082 |
| 0.0509 | 26 | 0.1767 | - | - |
| 0.0528 | 27 | 0.1951 | - | - |
| 0.0548 | 28 | 0.1621 | - | - |
| 0.0568 | 29 | 0.221 | - | - |
| 0.0587 | 30 | 0.2241 | 0.1435 | 0.9083 |
| 0.0607 | 31 | 0.2093 | - | - |
| 0.0626 | 32 | 0.1615 | - | - |
| 0.0646 | 33 | 0.1615 | - | - |
| 0.0665 | 34 | 0.1772 | - | - |
| 0.0685 | 35 | 0.2324 | 0.1423 | 0.9084 |
| 0.0705 | 36 | 0.2611 | - | - |
| 0.0724 | 37 | 0.214 | - | - |
| 0.0744 | 38 | 0.1985 | - | - |
| 0.0763 | 39 | 0.1855 | - | - |
| 0.0783 | 40 | 0.1234 | 0.1410 | 0.9085 |
| 0.0802 | 41 | 0.1492 | - | - |
| 0.0822 | 42 | 0.2022 | - | - |
| 0.0841 | 43 | 0.2146 | - | - |
| 0.0861 | 44 | 0.1688 | - | - |
| 0.0881 | 45 | 0.175 | 0.1396 | 0.9087 |
| 0.0900 | 46 | 0.2123 | - | - |
| 0.0920 | 47 | 0.1118 | - | - |
| 0.0939 | 48 | 0.3009 | - | - |
| 0.0959 | 49 | 0.1071 | - | - |
| 0.0978 | 50 | 0.2608 | 0.1382 | 0.9085 |
| 0.0998 | 51 | 0.1368 | - | - |
| 0.1018 | 52 | 0.2307 | - | - |
| 0.1037 | 53 | 0.1366 | - | - |
| 0.1057 | 54 | 0.1857 | - | - |
| 0.1076 | 55 | 0.2155 | 0.1367 | 0.9085 |
| 0.1096 | 56 | 0.2022 | - | - |
| 0.1115 | 57 | 0.2076 | - | - |
| 0.1135 | 58 | 0.4133 | - | - |
| 0.1155 | 59 | 0.1823 | - | - |
| 0.1174 | 60 | 0.1136 | 0.1353 | 0.9088 |
| 0.1194 | 61 | 0.1687 | - | - |
| 0.1213 | 62 | 0.1591 | - | - |
| 0.1233 | 63 | 0.1653 | - | - |
| 0.1252 | 64 | 0.1799 | - | - |
| 0.1272 | 65 | 0.1578 | 0.1337 | 0.9090 |
| 0.1292 | 66 | 0.1844 | - | - |
| 0.1311 | 67 | 0.1489 | - | - |
| 0.1331 | 68 | 0.1845 | - | - |
| 0.1350 | 69 | 0.1364 | - | - |
| 0.1370 | 70 | 0.1584 | 0.1321 | 0.9086 |
| 0.1389 | 71 | 0.2279 | - | - |
| 0.1409 | 72 | 0.2028 | - | - |
| 0.1429 | 73 | 0.2291 | - | - |
| 0.1448 | 74 | 0.2419 | - | - |
| 0.1468 | 75 | 0.1329 | 0.1306 | 0.9083 |
| 0.1487 | 76 | 0.204 | - | - |
| 0.1507 | 77 | 0.2239 | - | - |
| 0.1526 | 78 | 0.2181 | - | - |
| 0.1546 | 79 | 0.1285 | - | - |
| 0.1566 | 80 | 0.1067 | 0.1292 | 0.9079 |
| 0.1585 | 81 | 0.1189 | - | - |
| 0.1605 | 82 | 0.236 | - | - |
| 0.1624 | 83 | 0.1584 | - | - |
| 0.1644 | 84 | 0.1925 | - | - |
| 0.1663 | 85 | 0.129 | 0.1278 | 0.9079 |
| 0.1683 | 86 | 0.1376 | - | - |
| 0.1703 | 87 | 0.1691 | - | - |
| 0.1722 | 88 | 0.1045 | - | - |
| 0.1742 | 89 | 0.165 | - | - |
| 0.1761 | 90 | 0.2926 | 0.1267 | 0.9076 |
| 0.1781 | 91 | 0.1048 | - | - |
| 0.1800 | 92 | 0.1596 | - | - |
| 0.1820 | 93 | 0.2474 | - | - |
| 0.1840 | 94 | 0.1652 | - | - |
| 0.1859 | 95 | 0.2483 | 0.1253 | 0.9076 |
| 0.1879 | 96 | 0.1623 | - | - |
| 0.1898 | 97 | 0.1955 | - | - |
| 0.1918 | 98 | 0.2023 | - | - |
| 0.1937 | 99 | 0.1886 | - | - |
| 0.1957 | 100 | 0.1284 | 0.1229 | 0.9079 |
| 0.1977 | 101 | 0.2005 | - | - |
| 0.1996 | 102 | 0.2301 | - | - |
| 0.2016 | 103 | 0.2249 | - | - |
| 0.2035 | 104 | 0.214 | - | - |
| 0.2055 | 105 | 0.1429 | 0.1208 | 0.9077 |
| 0.2074 | 106 | 0.17 | - | - |
| 0.2094 | 107 | 0.1955 | - | - |
| 0.2114 | 108 | 0.1964 | - | - |
| 0.2133 | 109 | 0.1246 | - | - |
| 0.2153 | 110 | 0.1295 | 0.1190 | 0.9072 |
| 0.2172 | 111 | 0.2203 | - | - |
| 0.2192 | 112 | 0.2195 | - | - |
| 0.2211 | 113 | 0.1823 | - | - |
| 0.2231 | 114 | 0.174 | - | - |
| 0.2250 | 115 | 0.207 | 0.1175 | 0.9069 |
| 0.2270 | 116 | 0.2156 | - | - |
| 0.2290 | 117 | 0.2202 | - | - |
| 0.2309 | 118 | 0.2718 | - | - |
| 0.2329 | 119 | 0.1387 | - | - |
| 0.2348 | 120 | 0.1506 | 0.1168 | 0.9069 |
| 0.2368 | 121 | 0.1185 | - | - |
| 0.2387 | 122 | 0.1681 | - | - |
| 0.2407 | 123 | 0.2321 | - | - |
| 0.2427 | 124 | 0.1457 | - | - |
| 0.2446 | 125 | 0.2027 | 0.1165 | 0.9071 |
| 0.2466 | 126 | 0.1821 | - | - |
| 0.2485 | 127 | 0.1258 | - | - |
| 0.2505 | 128 | 0.184 | - | - |
| 0.2524 | 129 | 0.2015 | - | - |
| 0.2544 | 130 | 0.1323 | 0.1154 | 0.9074 |
| 0.2564 | 131 | 0.1939 | - | - |
| 0.2583 | 132 | 0.1428 | - | - |
| 0.2603 | 133 | 0.1063 | - | - |
| 0.2622 | 134 | 0.1602 | - | - |
| 0.2642 | 135 | 0.1814 | 0.1139 | 0.9067 |
| 0.2661 | 136 | 0.1518 | - | - |
| 0.2681 | 137 | 0.1379 | - | - |
| 0.2701 | 138 | 0.1708 | - | - |
| 0.2720 | 139 | 0.2046 | - | - |
| 0.2740 | 140 | 0.1259 | 0.1124 | 0.9063 |
| 0.2759 | 141 | 0.1181 | - | - |
| 0.2779 | 142 | 0.2144 | - | - |
| 0.2798 | 143 | 0.1822 | - | - |
| 0.2818 | 144 | 0.1667 | - | - |
| 0.2838 | 145 | 0.0779 | 0.1118 | 0.9060 |
| 0.2857 | 146 | 0.147 | - | - |
| 0.2877 | 147 | 0.1913 | - | - |
| 0.2896 | 148 | 0.1357 | - | - |
| 0.2916 | 149 | 0.1128 | - | - |
| 0.2935 | 150 | 0.0996 | 0.1113 | 0.9054 |
| 0.2955 | 151 | 0.1956 | - | - |
| 0.2975 | 152 | 0.0942 | - | - |
| 0.2994 | 153 | 0.1406 | - | - |
| 0.3014 | 154 | 0.2868 | - | - |
| 0.3033 | 155 | 0.1102 | 0.1114 | 0.9048 |
| 0.3053 | 156 | 0.1659 | - | - |
| 0.3072 | 157 | 0.1645 | - | - |
| 0.3092 | 158 | 0.151 | - | - |
| 0.3112 | 159 | 0.158 | - | - |
| 0.3131 | 160 | 0.2323 | 0.1113 | 0.9048 |
| 0.3151 | 161 | 0.1157 | - | - |
| 0.3170 | 162 | 0.1507 | - | - |
| 0.3190 | 163 | 0.1879 | - | - |
| 0.3209 | 164 | 0.143 | - | - |
| 0.3229 | 165 | 0.2227 | 0.1116 | 0.9050 |
| 0.3249 | 166 | 0.1624 | - | - |
| 0.3268 | 167 | 0.1345 | - | - |
| 0.3288 | 168 | 0.1765 | - | - |
| 0.3307 | 169 | 0.1368 | - | - |
| 0.3327 | 170 | 0.0962 | 0.1113 | 0.9056 |
| 0.3346 | 171 | 0.1783 | - | - |
| 0.3366 | 172 | 0.2019 | - | - |
| 0.3386 | 173 | 0.1761 | - | - |
| 0.3405 | 174 | 0.1855 | - | - |
| 0.3425 | 175 | 0.1922 | 0.1106 | 0.9054 |
| 0.3444 | 176 | 0.1538 | - | - |
| 0.3464 | 177 | 0.1049 | - | - |
| 0.3483 | 178 | 0.1619 | - | - |
| 0.3503 | 179 | 0.0731 | - | - |
| 0.3523 | 180 | 0.1205 | 0.1097 | 0.9059 |
| 0.3542 | 181 | 0.169 | - | - |
| 0.3562 | 182 | 0.1688 | - | - |
| 0.3581 | 183 | 0.1274 | - | - |
| 0.3601 | 184 | 0.1477 | - | - |
| 0.3620 | 185 | 0.1418 | 0.1094 | 0.9055 |
| 0.3640 | 186 | 0.2477 | - | - |
| 0.3659 | 187 | 0.1713 | - | - |
| 0.3679 | 188 | 0.1703 | - | - |
| 0.3699 | 189 | 0.1176 | - | - |
| 0.3718 | 190 | 0.1811 | 0.1084 | 0.9048 |
| 0.3738 | 191 | 0.162 | - | - |
| 0.3757 | 192 | 0.1141 | - | - |
| 0.3777 | 193 | 0.154 | - | - |
| 0.3796 | 194 | 0.2461 | - | - |
| 0.3816 | 195 | 0.1573 | 0.1076 | 0.9046 |
| 0.3836 | 196 | 0.1197 | - | - |
| 0.3855 | 197 | 0.1395 | - | - |
| 0.3875 | 198 | 0.0847 | - | - |
| 0.3894 | 199 | 0.1848 | - | - |
| 0.3914 | 200 | 0.1377 | 0.1072 | 0.9047 |
| 0.3933 | 201 | 0.1109 | - | - |
| 0.3953 | 202 | 0.1051 | - | - |
| 0.3973 | 203 | 0.0975 | - | - |
| 0.3992 | 204 | 0.127 | - | - |
| 0.4012 | 205 | 0.1297 | 0.1069 | 0.9049 |
| 0.4031 | 206 | 0.0783 | - | - |
| 0.4051 | 207 | 0.053 | - | - |
| 0.4070 | 208 | 0.1916 | - | - |
| 0.4090 | 209 | 0.178 | - | - |
| 0.4110 | 210 | 0.2343 | 0.1067 | 0.9053 |
| 0.4129 | 211 | 0.1816 | - | - |
| 0.4149 | 212 | 0.2522 | - | - |
| 0.4168 | 213 | 0.1787 | - | - |
| 0.4188 | 214 | 0.1913 | - | - |
| 0.4207 | 215 | 0.175 | 0.1055 | 0.9056 |
| 0.4227 | 216 | 0.1533 | - | - |
| 0.4247 | 217 | 0.1819 | - | - |
| 0.4266 | 218 | 0.2541 | - | - |
| 0.4286 | 219 | 0.1103 | - | - |
| 0.4305 | 220 | 0.1693 | 0.1040 | 0.9062 |
| 0.4325 | 221 | 0.1233 | - | - |
| 0.4344 | 222 | 0.0922 | - | - |
| 0.4364 | 223 | 0.1243 | - | - |
| 0.4384 | 224 | 0.1613 | - | - |
| 0.4403 | 225 | 0.1188 | 0.1030 | 0.9065 |
| 0.4423 | 226 | 0.196 | - | - |
| 0.4442 | 227 | 0.2254 | - | - |
| 0.4462 | 228 | 0.1162 | - | - |
| 0.4481 | 229 | 0.2579 | - | - |
| 0.4501 | 230 | 0.1203 | 0.1029 | 0.9071 |
| 0.4521 | 231 | 0.1654 | - | - |
| 0.4540 | 232 | 0.1808 | - | - |
| 0.4560 | 233 | 0.1397 | - | - |
| 0.4579 | 234 | 0.2177 | - | - |
| 0.4599 | 235 | 0.162 | 0.1040 | 0.9078 |
| 0.4618 | 236 | 0.177 | - | - |
| 0.4638 | 237 | 0.0556 | - | - |
| 0.4658 | 238 | 0.2285 | - | - |
| 0.4677 | 239 | 0.1657 | - | - |
| 0.4697 | 240 | 0.2555 | 0.1053 | 0.9077 |
| 0.4716 | 241 | 0.1606 | - | - |
| 0.4736 | 242 | 0.1257 | - | - |
| 0.4755 | 243 | 0.1898 | - | - |
| 0.4775 | 244 | 0.1621 | - | - |
| 0.4795 | 245 | 0.1606 | 0.1054 | 0.9079 |
| 0.4814 | 246 | 0.0983 | - | - |
| 0.4834 | 247 | 0.2028 | - | - |
| 0.4853 | 248 | 0.0997 | - | - |
| 0.4873 | 249 | 0.1582 | - | - |
| 0.4892 | 250 | 0.2394 | 0.1052 | 0.9074 |
| 0.4912 | 251 | 0.2186 | - | - |
| 0.4932 | 252 | 0.0993 | - | - |
| 0.4951 | 253 | 0.1805 | - | - |
| 0.4971 | 254 | 0.1178 | - | - |
| 0.4990 | 255 | 0.2198 | 0.1043 | 0.9070 |
| 0.5010 | 256 | 0.1064 | - | - |
| 0.5029 | 257 | 0.1436 | - | - |
| 0.5049 | 258 | 0.0859 | - | - |
| 0.5068 | 259 | 0.2157 | - | - |
| 0.5088 | 260 | 0.1455 | 0.1029 | 0.9058 |
| 0.5108 | 261 | 0.1974 | - | - |
| 0.5127 | 262 | 0.1667 | - | - |
| 0.5147 | 263 | 0.1512 | - | - |
| 0.5166 | 264 | 0.1684 | - | - |
| 0.5186 | 265 | 0.2132 | 0.1012 | 0.9053 |
| 0.5205 | 266 | 0.1645 | - | - |
| 0.5225 | 267 | 0.203 | - | - |
| 0.5245 | 268 | 0.1539 | - | - |
| 0.5264 | 269 | 0.1445 | - | - |
| 0.5284 | 270 | 0.1377 | 0.0994 | 0.9056 |
| 0.5303 | 271 | 0.1719 | - | - |
| 0.5323 | 272 | 0.1896 | - | - |
| 0.5342 | 273 | 0.1452 | - | - |
| 0.5362 | 274 | 0.1275 | - | - |
| 0.5382 | 275 | 0.1883 | 0.0980 | 0.9057 |
| 0.5401 | 276 | 0.1462 | - | - |
| 0.5421 | 277 | 0.1595 | - | - |
| 0.5440 | 278 | 0.1693 | - | - |
| 0.5460 | 279 | 0.1929 | - | - |
| 0.5479 | 280 | 0.154 | 0.0970 | 0.9053 |
| 0.5499 | 281 | 0.1468 | - | - |
| 0.5519 | 282 | 0.0898 | - | - |
| 0.5538 | 283 | 0.1425 | - | - |
| 0.5558 | 284 | 0.1362 | - | - |
| 0.5577 | 285 | 0.1025 | 0.0978 | 0.9053 |
| 0.5597 | 286 | 0.1578 | - | - |
| 0.5616 | 287 | 0.1235 | - | - |
| 0.5636 | 288 | 0.1109 | - | - |
| 0.5656 | 289 | 0.0746 | - | - |
| 0.5675 | 290 | 0.1471 | 0.0992 | 0.9053 |
| 0.5695 | 291 | 0.2631 | - | - |
| 0.5714 | 292 | 0.11 | - | - |
| 0.5734 | 293 | 0.1834 | - | - |
| 0.5753 | 294 | 0.1277 | - | - |
| 0.5773 | 295 | 0.2104 | 0.0990 | 0.9042 |
| 0.5793 | 296 | 0.1294 | - | - |
| 0.5812 | 297 | 0.1672 | - | - |
| 0.5832 | 298 | 0.2171 | - | - |
| 0.5851 | 299 | 0.1451 | - | - |
| 0.5871 | 300 | 0.0871 | 0.0980 | 0.9033 |
| 0.5890 | 301 | 0.0897 | - | - |
| 0.5910 | 302 | 0.1296 | - | - |
| 0.5930 | 303 | 0.1206 | - | - |
| 0.5949 | 304 | 0.1665 | - | - |
| 0.5969 | 305 | 0.1511 | 0.0979 | 0.9032 |
| 0.5988 | 306 | 0.1566 | - | - |
| 0.6008 | 307 | 0.1339 | - | - |
| 0.6027 | 308 | 0.1474 | - | - |
| 0.6047 | 309 | 0.1022 | - | - |
| 0.6067 | 310 | 0.1263 | 0.0983 | 0.9043 |
| 0.6086 | 311 | 0.1713 | - | - |
| 0.6106 | 312 | 0.1628 | - | - |
| 0.6125 | 313 | 0.1585 | - | - |
| 0.6145 | 314 | 0.1419 | - | - |
| 0.6164 | 315 | 0.1136 | 0.0983 | 0.9040 |
| 0.6184 | 316 | 0.255 | - | - |
| 0.6204 | 317 | 0.1262 | - | - |
| 0.6223 | 318 | 0.1393 | - | - |
| 0.6243 | 319 | 0.1134 | - | - |
| 0.6262 | 320 | 0.1441 | 0.0984 | 0.9033 |
| 0.6282 | 321 | 0.1744 | - | - |
| 0.6301 | 322 | 0.2124 | - | - |
| 0.6321 | 323 | 0.1267 | - | - |
| 0.6341 | 324 | 0.1435 | - | - |
| 0.6360 | 325 | 0.1705 | 0.0989 | 0.9023 |
| 0.6380 | 326 | 0.1441 | - | - |
| 0.6399 | 327 | 0.118 | - | - |
| 0.6419 | 328 | 0.1956 | - | - |
| 0.6438 | 329 | 0.0803 | - | - |
| 0.6458 | 330 | 0.1651 | 0.0991 | 0.9022 |
| 0.6477 | 331 | 0.1498 | - | - |
| 0.6497 | 332 | 0.1171 | - | - |
| 0.6517 | 333 | 0.1976 | - | - |
| 0.6536 | 334 | 0.0926 | - | - |
| 0.6556 | 335 | 0.1496 | 0.0991 | 0.9026 |
| 0.6575 | 336 | 0.1131 | - | - |
| 0.6595 | 337 | 0.1352 | - | - |
| 0.6614 | 338 | 0.1608 | - | - |
| 0.6634 | 339 | 0.1239 | - | - |
| 0.6654 | 340 | 0.1227 | 0.0993 | 0.9019 |
| 0.6673 | 341 | 0.1452 | - | - |
| 0.6693 | 342 | 0.1992 | - | - |
| 0.6712 | 343 | 0.1349 | - | - |
| 0.6732 | 344 | 0.1702 | - | - |
| 0.6751 | 345 | 0.1033 | 0.0990 | 0.9022 |
| 0.6771 | 346 | 0.1788 | - | - |
| 0.6791 | 347 | 0.1084 | - | - |
| 0.6810 | 348 | 0.1325 | - | - |
| 0.6830 | 349 | 0.1537 | - | - |
| 0.6849 | 350 | 0.2099 | 0.0989 | 0.9022 |
| 0.6869 | 351 | 0.1603 | - | - |
| 0.6888 | 352 | 0.0982 | - | - |
| 0.6908 | 353 | 0.1537 | - | - |
| 0.6928 | 354 | 0.1758 | - | - |
| 0.6947 | 355 | 0.1521 | 0.0990 | 0.9019 |
| 0.6967 | 356 | 0.089 | - | - |
| 0.6986 | 357 | 0.1509 | - | - |
| 0.7006 | 358 | 0.1943 | - | - |
| 0.7025 | 359 | 0.1582 | - | - |
| 0.7045 | 360 | 0.1527 | 0.0993 | 0.9008 |
| 0.7065 | 361 | 0.0754 | - | - |
| 0.7084 | 362 | 0.122 | - | - |
| 0.7104 | 363 | 0.1727 | - | - |
| 0.7123 | 364 | 0.074 | - | - |
| 0.7143 | 365 | 0.1822 | 0.0998 | 0.9005 |
| 0.7162 | 366 | 0.1344 | - | - |
| 0.7182 | 367 | 0.1819 | - | - |
| 0.7202 | 368 | 0.1811 | - | - |
| 0.7221 | 369 | 0.1564 | - | - |
| 0.7241 | 370 | 0.1522 | 0.0997 | 0.8998 |
| 0.7260 | 371 | 0.1379 | - | - |
| 0.7280 | 372 | 0.082 | - | - |
| 0.7299 | 373 | 0.1288 | - | - |
| 0.7319 | 374 | 0.1809 | - | - |
| 0.7339 | 375 | 0.2418 | 0.0991 | 0.9006 |
| 0.7358 | 376 | 0.0789 | - | - |
| 0.7378 | 377 | 0.132 | - | - |
| 0.7397 | 378 | 0.1425 | - | - |
| 0.7417 | 379 | 0.1514 | - | - |
| 0.7436 | 380 | 0.0997 | 0.0984 | 0.9018 |
| 0.7456 | 381 | 0.2002 | - | - |
| 0.7476 | 382 | 0.1943 | - | - |
| 0.7495 | 383 | 0.1198 | - | - |
| 0.7515 | 384 | 0.1171 | - | - |
| 0.7534 | 385 | 0.0872 | 0.0978 | 0.9026 |
| 0.7554 | 386 | 0.0937 | - | - |
| 0.7573 | 387 | 0.0933 | - | - |
| 0.7593 | 388 | 0.1109 | - | - |
| 0.7613 | 389 | 0.0999 | - | - |
| 0.7632 | 390 | 0.1625 | 0.0973 | 0.9034 |
| 0.7652 | 391 | 0.1357 | - | - |
| 0.7671 | 392 | 0.1202 | - | - |
| 0.7691 | 393 | 0.116 | - | - |
| 0.7710 | 394 | 0.1256 | - | - |
| 0.7730 | 395 | 0.2402 | 0.0969 | 0.9037 |
| 0.7750 | 396 | 0.2413 | - | - |
| 0.7769 | 397 | 0.1144 | - | - |
| 0.7789 | 398 | 0.1198 | - | - |
| 0.7808 | 399 | 0.1361 | - | - |
| 0.7828 | 400 | 0.1496 | 0.0964 | 0.9038 |
| 0.7847 | 401 | 0.1606 | - | - |
| 0.7867 | 402 | 0.1739 | - | - |
| 0.7886 | 403 | 0.1121 | - | - |
| 0.7906 | 404 | 0.1176 | - | - |
| 0.7926 | 405 | 0.1024 | 0.0955 | 0.9034 |
| 0.7945 | 406 | 0.1256 | - | - |
| 0.7965 | 407 | 0.1424 | - | - |
| 0.7984 | 408 | 0.181 | - | - |
| 0.8004 | 409 | 0.0829 | - | - |
| 0.8023 | 410 | 0.2329 | 0.0949 | 0.9032 |
| 0.8043 | 411 | 0.075 | - | - |
| 0.8063 | 412 | 0.1157 | - | - |
| 0.8082 | 413 | 0.1383 | - | - |
| 0.8102 | 414 | 0.1042 | - | - |
| 0.8121 | 415 | 0.1352 | 0.0943 | 0.9025 |
| 0.8141 | 416 | 0.0778 | - | - |
| 0.8160 | 417 | 0.1006 | - | - |
| 0.8180 | 418 | 0.2188 | - | - |
| 0.8200 | 419 | 0.1338 | - | - |
| 0.8219 | 420 | 0.1314 | 0.0940 | 0.9023 |
| 0.8239 | 421 | 0.1298 | - | - |
| 0.8258 | 422 | 0.1573 | - | - |
| 0.8278 | 423 | 0.1283 | - | - |
| 0.8297 | 424 | 0.1998 | - | - |
| 0.8317 | 425 | 0.0747 | 0.0939 | 0.9019 |
| 0.8337 | 426 | 0.142 | - | - |
| 0.8356 | 427 | 0.131 | - | - |
| 0.8376 | 428 | 0.1037 | - | - |
| 0.8395 | 429 | 0.1145 | - | - |
| 0.8415 | 430 | 0.1371 | 0.0939 | 0.9020 |
| 0.8434 | 431 | 0.1457 | - | - |
| 0.8454 | 432 | 0.123 | - | - |
| 0.8474 | 433 | 0.1312 | - | - |
| 0.8493 | 434 | 0.1301 | - | - |
| 0.8513 | 435 | 0.1324 | 0.0940 | 0.9021 |
| 0.8532 | 436 | 0.1826 | - | - |
| 0.8552 | 437 | 0.2145 | - | - |
| 0.8571 | 438 | 0.132 | - | - |
| 0.8591 | 439 | 0.1263 | - | - |
| 0.8611 | 440 | 0.1461 | 0.0942 | 0.9022 |
| 0.8630 | 441 | 0.1349 | - | - |
| 0.8650 | 442 | 0.0824 | - | - |
| 0.8669 | 443 | 0.1639 | - | - |
| 0.8689 | 444 | 0.1403 | - | - |
| 0.8708 | 445 | 0.1766 | 0.0943 | 0.9024 |
| 0.8728 | 446 | 0.1402 | - | - |
| 0.8748 | 447 | 0.1203 | - | - |
| 0.8767 | 448 | 0.1398 | - | - |
| 0.8787 | 449 | 0.2226 | - | - |
| 0.8806 | 450 | 0.0943 | 0.0943 | 0.9024 |
| 0.8826 | 451 | 0.1101 | - | - |
| 0.8845 | 452 | 0.1536 | - | - |
| 0.8865 | 453 | 0.1159 | - | - |
| 0.8885 | 454 | 0.1373 | - | - |
| 0.8904 | 455 | 0.1412 | 0.0943 | 0.9026 |
| 0.8924 | 456 | 0.0626 | - | - |
| 0.8943 | 457 | 0.1447 | - | - |
| 0.8963 | 458 | 0.1296 | - | - |
| 0.8982 | 459 | 0.1407 | - | - |
| 0.9002 | 460 | 0.1966 | 0.0943 | 0.9026 |
| 0.9022 | 461 | 0.1019 | - | - |
| 0.9041 | 462 | 0.1332 | - | - |
| 0.9061 | 463 | 0.1417 | - | - |
| 0.9080 | 464 | 0.1782 | - | - |
| 0.9100 | 465 | 0.1068 | 0.0943 | 0.9025 |
| 0.9119 | 466 | 0.1292 | - | - |
| 0.9139 | 467 | 0.1896 | - | - |
| 0.9159 | 468 | 0.1597 | - | - |
| 0.9178 | 469 | 0.1588 | - | - |
| 0.9198 | 470 | 0.13 | 0.0942 | 0.9026 |
| 0.9217 | 471 | 0.1593 | - | - |
| 0.9237 | 472 | 0.1137 | - | - |
| 0.9256 | 473 | 0.1295 | - | - |
| 0.9276 | 474 | 0.1367 | - | - |
| 0.9295 | 475 | 0.107 | 0.0942 | 0.9025 |
| 0.9315 | 476 | 0.1442 | - | - |
| 0.9335 | 477 | 0.1841 | - | - |
| 0.9354 | 478 | 0.0436 | - | - |
| 0.9374 | 479 | 0.0908 | - | - |
| 0.9393 | 480 | 0.1233 | 0.0941 | 0.9026 |
| 0.9413 | 481 | 0.1676 | - | - |
| 0.9432 | 482 | 0.1449 | - | - |
| 0.9452 | 483 | 0.1234 | - | - |
| 0.9472 | 484 | 0.076 | - | - |
| 0.9491 | 485 | 0.1369 | 0.0941 | 0.9026 |
| 0.9511 | 486 | 0.144 | - | - |
| 0.9530 | 487 | 0.0874 | - | - |
| 0.9550 | 488 | 0.195 | - | - |
| 0.9569 | 489 | 0.1585 | - | - |
| 0.9589 | 490 | 0.1152 | 0.0941 | 0.9027 |
| 0.9609 | 491 | 0.0862 | - | - |
| 0.9628 | 492 | 0.2244 | - | - |
| 0.9648 | 493 | 0.0987 | - | - |
| 0.9667 | 494 | 0.105 | - | - |
| 0.9687 | 495 | 0.1777 | 0.0940 | 0.9026 |
| 0.9706 | 496 | 0.1838 | - | - |
| 0.9726 | 497 | 0.1813 | - | - |
| 0.9746 | 498 | 0.0994 | - | - |
| 0.9765 | 499 | 0.1576 | - | - |
| 0.9785 | 500 | 0.1298 | 0.0940 | 0.9027 |
| 0.9804 | 501 | 0.1884 | - | - |
| 0.9824 | 502 | 0.1032 | - | - |
| 0.9843 | 503 | 0.1164 | - | - |
| 0.9863 | 504 | 0.1466 | - | - |
| 0.9883 | 505 | 0.2192 | 0.0940 | 0.9027 |
| 0.9902 | 506 | 0.1302 | - | - |
| 0.9922 | 507 | 0.1371 | - | - |
| 0.9941 | 508 | 0.1543 | - | - |
| 0.9961 | 509 | 0.1084 | - | - |
| 0.9980 | 510 | 0.0 | 0.0940 | 0.9027 |
| 1.0 | 511 | 0.0 | - | - |
| 1.0020 | 512 | 0.0 | - | - |
| 1.0039 | 513 | 0.0 | - | - |
| 1.0059 | 514 | 0.0 | - | - |
| 1.0078 | 515 | 0.0 | 0.0938 | 0.9030 |
</details>
### Framework Versions
- Python: 3.10.14
- Sentence Transformers: 3.0.1
- Transformers: 4.44.0
- PyTorch: 2.4.0
- Accelerate: 0.33.0
- Datasets: 2.21.0
- Tokenizers: 0.19.1
## Citation
### BibTeX
#### Sentence Transformers
```bibtex
@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",
}
```
<!--
## Glossary
*Clearly define terms in order to be accessible across audiences.*
-->
<!--
## Model Card Authors
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
-->
<!--
## Model Card Contact
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
--> |