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tomaarsen
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ms-marco-ettin-150m-reranker

Text Ranking
sentence-transformers
Safetensors
English
modernbert
cross-encoder
reranker
Generated from Trainer
dataset_size:39770704
loss:MarginMSELoss
Eval Results
Model card Files
xet
Community

CrossEncoder based on jhu-clsp/ettin-encoder-150m

This is a Cross Encoder model finetuned from jhu-clsp/ettin-encoder-150m on the msmarco dataset using the sentence-transformers library. It computes scores for pairs of texts, which can be used for text reranking and semantic search.

Model Details

Model Description

  • Model Type: Cross Encoder
  • Base model: jhu-clsp/ettin-encoder-150m
  • Maximum Sequence Length: 512 tokens
  • Number of Output Labels: 1 label
  • Training Dataset:
  • Language: en

Model Sources

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 CrossEncoder

# Download from the 🤗 Hub
model = CrossEncoder("tomaarsen/ms-marco-ettin-150m-reranker")
# Get scores for pairs of texts
pairs = [
    ['which constitutional amendment required that u.s. senators be directly elected by the people instead of being chosen by state legislatures?', 'Full text of the Constitution and Amendments. The Seventeenth Amendment (Amendment XVII) to the United States Constitution established the popular election of United States Senators by the people of the states. The amendment supersedes Article I, §3, Clauses 1 and 2 of the Constitution, under which senators were elected by state legislatures. It also alters the procedure for filling vacancies in the Senate, allowing for state legislatures to permit their governors to make temporary appointments until a special election can be held.'],
    ['where is the tigris river?', 'The Tigris is one of the two main rivers of Mesopotamia (modern Iraq). The Tigris is the river to the east (towards Persia [modern Iran]); the Euphrates, to the west. The Tigris runs from Lake Hazar, in the Taurus Mountains, in Turkey, joins the Euphrates, and flows into the Persian Gulf. The Encyclopedia Britannica says the Tigris is 1,180 miles (1,900 km) in length.'],
    ['what tectonic plate is japan on', 'Japan lies over 4 tectonic plates. These are: The North American Plate The Eurasian Plate The Philippine Sea Plate The Pacific Plate.+ 5 others found this useful.Nathaniel Preece.apan lies on the North American, Eurasian and Pacific plates, and is close to the Phillipine plate. Tokyo and Sendai, for example are on the North American plate.'],
    ['how many seasons of portlandia are there', 'We monitor the news to keep you updated on the release date of Portlandia season 7. To the delight of the fans, IFC has officially renewed the series. The release date has not been scheduled yet. If you want to get automatically notified of the showâ\x80\x99s premiere date, please, sign up for updates below.'],
    ['how to delete messenger messages from iphone', 'Tap the Facebook Messengerâ\x80\x9d application and select Messages tab. 2. Locate the message or messages that you wish to delete. Press and hold on the message until a list of options displays, including the option to delete or copy the message. 3. Choose the Delete tab, not the Archive tab. If you wish to permanently delete Facebook messages, tap the Delete option.'],
]
scores = model.predict(pairs)
print(scores.shape)
# (5,)

# Or rank different texts based on similarity to a single text
ranks = model.rank(
    'which constitutional amendment required that u.s. senators be directly elected by the people instead of being chosen by state legislatures?',
    [
        'Full text of the Constitution and Amendments. The Seventeenth Amendment (Amendment XVII) to the United States Constitution established the popular election of United States Senators by the people of the states. The amendment supersedes Article I, §3, Clauses 1 and 2 of the Constitution, under which senators were elected by state legislatures. It also alters the procedure for filling vacancies in the Senate, allowing for state legislatures to permit their governors to make temporary appointments until a special election can be held.',
        'The Tigris is one of the two main rivers of Mesopotamia (modern Iraq). The Tigris is the river to the east (towards Persia [modern Iran]); the Euphrates, to the west. The Tigris runs from Lake Hazar, in the Taurus Mountains, in Turkey, joins the Euphrates, and flows into the Persian Gulf. The Encyclopedia Britannica says the Tigris is 1,180 miles (1,900 km) in length.',
        'Japan lies over 4 tectonic plates. These are: The North American Plate The Eurasian Plate The Philippine Sea Plate The Pacific Plate.+ 5 others found this useful.Nathaniel Preece.apan lies on the North American, Eurasian and Pacific plates, and is close to the Phillipine plate. Tokyo and Sendai, for example are on the North American plate.',
        'We monitor the news to keep you updated on the release date of Portlandia season 7. To the delight of the fans, IFC has officially renewed the series. The release date has not been scheduled yet. If you want to get automatically notified of the showâ\x80\x99s premiere date, please, sign up for updates below.',
        'Tap the Facebook Messengerâ\x80\x9d application and select Messages tab. 2. Locate the message or messages that you wish to delete. Press and hold on the message until a list of options displays, including the option to delete or copy the message. 3. Choose the Delete tab, not the Archive tab. If you wish to permanently delete Facebook messages, tap the Delete option.',
    ]
)
# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]

Evaluation

Metrics

Cross Encoder Reranking

  • Datasets: NanoMSMARCO_R100, NanoNFCorpus_R100 and NanoNQ_R100
  • Evaluated with CrossEncoderRerankingEvaluator with these parameters:
    {
    "at_k": 10,
    "always_rerank_positives": true
}
Metric NanoMSMARCO_R100 NanoNFCorpus_R100 NanoNQ_R100
map 0.6522 (+0.1627) 0.3763 (+0.1153) 0.7584 (+0.3388)
mrr@10 0.6477 (+0.1702) 0.6256 (+0.1258) 0.7881 (+0.3614)
ndcg@10 0.7180 (+0.1776) 0.4451 (+0.1201) 0.8011 (+0.3005)

Cross Encoder Nano BEIR

  • Dataset: NanoBEIR_R100_mean
  • Evaluated with CrossEncoderNanoBEIREvaluator with these parameters:
    {
    "dataset_names": [
        "msmarco",
        "nfcorpus",
        "nq"
    ],
    "rerank_k": 100,
    "at_k": 10,
    "always_rerank_positives": true
}
Metric Value
map 0.5957 (+0.2056)
mrr@10 0.6871 (+0.2191)
ndcg@10 0.6548 (+0.1994)

Training Details

Training Dataset

msmarco

  • Dataset: msmarco at 9e329ed
  • Size: 39,770,704 training samples
  • Columns: query_id, positive_id, negative_id, and score
  • Approximate statistics based on the first 1000 samples:
    query_id positive_id negative_id score
    type string string string float
    details
    • min: 10 characters
    • mean: 34.72 characters
    • max: 108 characters
    • min: 71 characters
    • mean: 351.58 characters
    • max: 919 characters
    • min: 81 characters
    • mean: 344.41 characters
    • max: 992 characters
    • min: -1.0
    • mean: 13.5
    • max: 22.59
  • Samples:
    query_id positive_id negative_id score
    where is jade city bc Jade City, British Columbia. From Wikipedia, the free encyclopedia. Jade City is a spot on the road in northwestern British Columbia, Canada, near the Yukon, located on Highway 37, west of Good Hope Lake and close to Cassiar, in the Cassiar Highlands.The region around Jade City is rich with serpentinite (a jade precursor), greenstone (jade look-a-likes), and jade.ade City is by road about 24 hours north of Vancouver, and 1 hour south of the Yukon border. As of 2015, it has a population of about 30 people. Jade City is a very small town. China. Few gems have the mystique of jade, a stone that has been revered in China for more than 4000 years. Jade is also one of the most misunderstood of gems -- there is widespread confusion about the types of jade, about the most valuable colors, and the standards used to grade it. 15.705843766530355
    is asparagus good for your kidneys Is Asparagus Good For Your Kidneys? Those who want to keep their kidneys functioning properly will definitely want to include certain foods in their diet, including asparagus. This particular vegetable is able to sooth the urinary system as well as increase urine production and support kidney function overall. Some of the different properties that asparagus has which makes it good for the kidneys includes asparagin, glycosides, glycolic acid, tyrosin, vitamin A, B, C, E and folic acid. Last year, I planted 20 asparagus crowns and only had 1 fern over the entire year. This year, I read a lot of articles on planting asparagus and decided to follow a recommendation to soak the crowns in luke warm water for 30 minutes before planting.reat article! Last year, I planted 20 asparagus crowns and only had 1 fern over the entire year. This year, I read a lot of articles on planting asparagus and decided to follow a recommendation to soak the crowns in luke warm water for 30 minutes before planting. Success! I now have ferns along the entire row! 21.735484917958576
    what does a urine culture tell you A urine culture is a test to find germs (such as bacteria) in the urine that can cause an infection. Urine in the bladder is normally sterile. This means it does not contain any bacteria or other organisms (such as fungi). But bacteria can enter the urethra and cause a urinary tract infection (UTI). What Is The Procedure To Conduct A Urine Culture Test? Urine culture refers to a urine test that is conducted to find bacteria that could cause a urinary tract infection. Bladder urine is supposed to be sterile and devoid of any bacteria or fungi, but sometimes bacteria enters the urine through the urethra, causing a urinary infection. 1.1982590357462568
  • Loss: MarginMSELoss with these parameters:
    {
    "activation_fn": "torch.nn.modules.linear.Identity"
}

Evaluation Dataset

msmarco

  • Dataset: msmarco at 9e329ed
  • Size: 10,000 evaluation samples
  • Columns: query_id, positive_id, negative_id, and score
  • Approximate statistics based on the first 1000 samples:
    query_id positive_id negative_id score
    type string string string float
    details
    • min: 8 characters
    • mean: 34.72 characters
    • max: 169 characters
    • min: 65 characters
    • mean: 356.17 characters
    • max: 968 characters
    • min: 36 characters
    • mean: 340.3 characters
    • max: 982 characters
    • min: -2.7
    • mean: 13.48
    • max: 22.44
  • Samples:
    query_id positive_id negative_id score
    which constitutional amendment required that u.s. senators be directly elected by the people instead of being chosen by state legislatures? Full text of the Constitution and Amendments. The Seventeenth Amendment (Amendment XVII) to the United States Constitution established the popular election of United States Senators by the people of the states. The amendment supersedes Article I, §3, Clauses 1 and 2 of the Constitution, under which senators were elected by state legislatures. It also alters the procedure for filling vacancies in the Senate, allowing for state legislatures to permit their governors to make temporary appointments until a special election can be held. Explanation: The original text of the Constitution called for the election of a state s senators to be dome by the state s legislature. This was changed in the 17th amendment that called for Senators to be elected directly by the people of the states. -0.32251540819803814
    where is the tigris river? The Tigris is one of the two main rivers of Mesopotamia (modern Iraq). The Tigris is the river to the east (towards Persia [modern Iran]); the Euphrates, to the west. The Tigris runs from Lake Hazar, in the Taurus Mountains, in Turkey, joins the Euphrates, and flows into the Persian Gulf. The Encyclopedia Britannica says the Tigris is 1,180 miles (1,900 km) in length. The oldest known civilization in South America, as well as in the Western Hemisphere as a whole, the Norte Chico civilization-c. 3200 BC - 1800 BC-comprised several interconnected settlements on the Peruvian coast, including the urban centers at Aspero and Caral.he civilizations that emerged around these rivers are among the earliest known non-nomadic agrarian societies. Because Ubaid, Sumer, Akkad, Assyria and Babylon civilizations all emerged around the Tigris-Euphrates, the theory that Mesopotamia is the cradle of civilization is widely accepted. 12.891789237658184
    what tectonic plate is japan on Japan lies over 4 tectonic plates. These are: The North American Plate The Eurasian Plate The Philippine Sea Plate The Pacific Plate.+ 5 others found this useful.Nathaniel Preece.apan lies on the North American, Eurasian and Pacific plates, and is close to the Phillipine plate. Tokyo and Sendai, for example are on the North American plate. History[edit] In the past two decades the steel plate shear wall (SPSW), also known as the steel plate wall (SPW), has been used in a number of buildings in Japan and North America as part of the lateral force resisting system. 12.691253264745075
  • Loss: MarginMSELoss with these parameters:
    {
    "activation_fn": "torch.nn.modules.linear.Identity"
}

Training Hyperparameters

Non-Default Hyperparameters

  • eval_strategy: steps
  • per_device_train_batch_size: 128
  • per_device_eval_batch_size: 128
  • learning_rate: 2e-05
  • num_train_epochs: 1
  • warmup_ratio: 0.1
  • seed: 12
  • bf16: True
  • load_best_model_at_end: True

All Hyperparameters

Click to expand
  • overwrite_output_dir: False
  • do_predict: False
  • eval_strategy: steps
  • prediction_loss_only: True
  • per_device_train_batch_size: 128
  • 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: 0.0
  • 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
  • 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: True
  • 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: True
  • 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

Click to expand
Epoch Step Training Loss Validation Loss NanoMSMARCO_R100_ndcg@10 NanoNFCorpus_R100_ndcg@10 NanoNQ_R100_ndcg@10 NanoBEIR_R100_mean_ndcg@10
-1 -1 - - 0.0321 (-0.5083) 0.1979 (-0.1271) 0.0227 (-0.4780) 0.0842 (-0.3711)
0.0000 1 207.4745 - - - - -
0.0020 78 208.2147 - - - - -
0.0040 156 206.6548 - - - - -
0.0060 234 200.7388 - - - - -
0.0080 312 182.4953 - - - - -
0.0100 389 - 75.3840 0.3932 (-0.1472) 0.2493 (-0.0758) 0.4066 (-0.0940) 0.3497 (-0.1057)
0.0100 390 130.2694 - - - - -
0.0121 468 43.6472 - - - - -
0.0141 546 24.7341 - - - - -
0.0161 624 18.6241 - - - - -
0.0181 702 15.3865 - - - - -
0.0200 778 - 12.5421 0.6049 (+0.0645) 0.3811 (+0.0561) 0.6413 (+0.1406) 0.5424 (+0.0871)
0.0201 780 13.24 - - - - -
0.0221 858 11.5539 - - - - -
0.0241 936 10.4097 - - - - -
0.0261 1014 9.5802 - - - - -
0.0281 1092 8.8313 - - - - -
0.0300 1167 - 8.2054 0.6507 (+0.1103) 0.3997 (+0.0746) 0.7045 (+0.2039) 0.5850 (+0.1296)
0.0301 1170 8.3729 - - - - -
0.0321 1248 7.8437 - - - - -
0.0341 1326 7.4383 - - - - -
0.0362 1404 6.9899 - - - - -
0.0382 1482 6.7353 - - - - -
0.0401 1556 - 6.4089 0.6421 (+0.1016) 0.4112 (+0.0861) 0.7289 (+0.2283) 0.5941 (+0.1387)
0.0402 1560 6.4088 - - - - -
0.0422 1638 6.1957 - - - - -
0.0442 1716 6.0008 - - - - -
0.0462 1794 5.7517 - - - - -
0.0482 1872 5.5172 - - - - -
0.0501 1945 - 5.5248 0.6704 (+0.1300) 0.4163 (+0.0913) 0.7344 (+0.2337) 0.6070 (+0.1517)
0.0502 1950 5.38 - - - - -
0.0522 2028 5.3785 - - - - -
0.0542 2106 5.1515 - - - - -
0.0562 2184 5.0263 - - - - -
0.0582 2262 4.9028 - - - - -
0.0601 2334 - 4.8510 0.6637 (+0.1233) 0.4187 (+0.0936) 0.7418 (+0.2412) 0.6081 (+0.1527)
0.0603 2340 4.8283 - - - - -
0.0623 2418 4.6962 - - - - -
0.0643 2496 4.6482 - - - - -
0.0663 2574 4.5224 - - - - -
0.0683 2652 4.4137 - - - - -
0.0701 2723 - 4.4682 0.6785 (+0.1381) 0.4142 (+0.0892) 0.7679 (+0.2672) 0.6202 (+0.1648)
0.0703 2730 4.3639 - - - - -
0.0723 2808 4.2902 - - - - -
0.0743 2886 4.2308 - - - - -
0.0763 2964 4.1607 - - - - -
0.0783 3042 4.0809 - - - - -
0.0801 3112 - 3.9937 0.6766 (+0.1362) 0.4238 (+0.0988) 0.7817 (+0.2810) 0.6274 (+0.1720)
0.0803 3120 4.0516 - - - - -
0.0823 3198 3.9772 - - - - -
0.0844 3276 3.9662 - - - - -
0.0864 3354 3.8161 - - - - -
0.0884 3432 3.8557 - - - - -
0.0901 3501 - 3.9840 0.6680 (+0.1276) 0.4198 (+0.0947) 0.7710 (+0.2703) 0.6196 (+0.1642)
0.0904 3510 3.7875 - - - - -
0.0924 3588 3.7164 - - - - -
0.0944 3666 3.6808 - - - - -
0.0964 3744 3.6347 - - - - -
0.0984 3822 3.5847 - - - - -
0.1002 3890 - 3.6954 0.6761 (+0.1357) 0.4364 (+0.1114) 0.7863 (+0.2856) 0.6329 (+0.1776)
0.1004 3900 3.5902 - - - - -
0.1024 3978 3.509 - - - - -
0.1044 4056 3.5064 - - - - -
0.1064 4134 3.4219 - - - - -
0.1085 4212 3.366 - - - - -
0.1102 4279 - 3.3804 0.6863 (+0.1459) 0.4224 (+0.0973) 0.7947 (+0.2941) 0.6345 (+0.1791)
0.1105 4290 3.3347 - - - - -
0.1125 4368 3.3026 - - - - -
0.1145 4446 3.2498 - - - - -
0.1165 4524 3.255 - - - - -
0.1185 4602 3.1982 - - - - -
0.1202 4668 - 3.2256 0.7017 (+0.1613) 0.4293 (+0.1043) 0.7822 (+0.2816) 0.6377 (+0.1824)
0.1205 4680 3.1525 - - - - -
0.1225 4758 3.1405 - - - - -
0.1245 4836 3.0912 - - - - -
0.1265 4914 3.0559 - - - - -
0.1285 4992 3.0431 - - - - -
0.1302 5057 - 3.0894 0.6808 (+0.1404) 0.4356 (+0.1106) 0.7973 (+0.2967) 0.6379 (+0.1825)
0.1305 5070 3.0138 - - - - -
0.1326 5148 3.0115 - - - - -
0.1346 5226 2.9885 - - - - -
0.1366 5304 2.933 - - - - -
0.1386 5382 2.885 - - - - -
0.1402 5446 - 2.9048 0.7014 (+0.1610) 0.4382 (+0.1131) 0.7868 (+0.2861) 0.6421 (+0.1867)
0.1406 5460 2.8851 - - - - -
0.1426 5538 2.9002 - - - - -
0.1446 5616 2.8765 - - - - -
0.1466 5694 2.8202 - - - - -
0.1486 5772 2.847 - - - - -
0.1502 5835 - 2.9050 0.7169 (+0.1764) 0.4233 (+0.0983) 0.7844 (+0.2838) 0.6415 (+0.1862)
0.1506 5850 2.8285 - - - - -
0.1526 5928 2.7882 - - - - -
0.1546 6006 2.7507 - - - - -
0.1567 6084 2.7457 - - - - -
0.1587 6162 2.7313 - - - - -
0.1603 6224 - 2.7971 0.7180 (+0.1776) 0.4451 (+0.1201) 0.8011 (+0.3005) 0.6548 (+0.1994)
0.1607 6240 2.7239 - - - - -
0.1627 6318 2.6975 - - - - -
0.1647 6396 2.6854 - - - - -
0.1667 6474 2.6714 - - - - -
0.1687 6552 2.6476 - - - - -
0.1703 6613 - 2.6787 0.7106 (+0.1702) 0.4325 (+0.1075) 0.7970 (+0.2964) 0.6467 (+0.1914)
0.1707 6630 2.6565 - - - - -
0.1727 6708 2.5863 - - - - -
0.1747 6786 2.6027 - - - - -
0.1767 6864 2.606 - - - - -
0.1787 6942 2.5634 - - - - -
0.1803 7002 - 2.6158 0.7166 (+0.1762) 0.4361 (+0.1111) 0.7984 (+0.2977) 0.6504 (+0.1950)
0.1808 7020 2.548 - - - - -
0.1828 7098 2.5719 - - - - -
0.1848 7176 2.5375 - - - - -
0.1868 7254 2.5263 - - - - -
0.1888 7332 2.5312 - - - - -
0.1903 7391 - 2.5446 0.7002 (+0.1598) 0.4387 (+0.1137) 0.7865 (+0.2859) 0.6418 (+0.1864)
0.1908 7410 2.4945 - - - - -
0.1928 7488 2.4464 - - - - -
0.1948 7566 2.4738 - - - - -
0.1968 7644 2.4752 - - - - -
0.1988 7722 2.4583 - - - - -
0.2003 7780 - 2.4624 0.6970 (+0.1565) 0.4396 (+0.1145) 0.7976 (+0.2970) 0.6447 (+0.1893)
0.2008 7800 2.4284 - - - - -
0.2028 7878 2.4296 - - - - -
0.2049 7956 2.4268 - - - - -
0.2069 8034 2.4424 - - - - -
0.2089 8112 2.4084 - - - - -
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0.8033 31200 1.4043 - - - - -
0.8053 31278 1.4123 - - - - -
0.8074 31356 1.4206 - - - - -
0.8094 31434 1.4043 - - - - -
0.8113 31509 - 1.3989 0.6856 (+0.1452) 0.4354 (+0.1103) 0.7752 (+0.2746) 0.6321 (+0.1767)
0.8114 31512 1.4099 - - - - -
0.8134 31590 1.3995 - - - - -
0.8154 31668 1.4002 - - - - -
0.8174 31746 1.3961 - - - - -
0.8194 31824 1.3848 - - - - -
0.8213 31898 - 1.3922 0.6864 (+0.1460) 0.4341 (+0.1090) 0.7734 (+0.2728) 0.6313 (+0.1760)
0.8214 31902 1.418 - - - - -
0.8234 31980 1.4076 - - - - -
0.8254 32058 1.3818 - - - - -
0.8274 32136 1.3747 - - - - -
0.8294 32214 1.3872 - - - - -
0.8313 32287 - 1.3914 0.6930 (+0.1526) 0.4386 (+0.1135) 0.7725 (+0.2718) 0.6347 (+0.1793)
0.8315 32292 1.3882 - - - - -
0.8335 32370 1.4111 - - - - -
0.8355 32448 1.3677 - - - - -
0.8375 32526 1.3726 - - - - -
0.8395 32604 1.377 - - - - -
0.8413 32676 - 1.3778 0.6842 (+0.1438) 0.4387 (+0.1136) 0.7823 (+0.2817) 0.6351 (+0.1797)
0.8415 32682 1.3853 - - - - -
0.8435 32760 1.3851 - - - - -
0.8455 32838 1.3724 - - - - -
0.8475 32916 1.3845 - - - - -
0.8495 32994 1.3827 - - - - -
0.8514 33065 - 1.3790 0.6848 (+0.1443) 0.4374 (+0.1124) 0.7797 (+0.2791) 0.6340 (+0.1786)
0.8515 33072 1.388 - - - - -
0.8535 33150 1.377 - - - - -
0.8556 33228 1.3762 - - - - -
0.8576 33306 1.3716 - - - - -
0.8596 33384 1.3763 - - - - -
0.8614 33454 - 1.3811 0.6874 (+0.1469) 0.4388 (+0.1138) 0.7727 (+0.2721) 0.6330 (+0.1776)
0.8616 33462 1.3755 - - - - -
0.8636 33540 1.3733 - - - - -
0.8656 33618 1.3621 - - - - -
0.8676 33696 1.3648 - - - - -
0.8696 33774 1.3665 - - - - -
0.8714 33843 - 1.3638 0.6905 (+0.1500) 0.4394 (+0.1143) 0.7755 (+0.2749) 0.6351 (+0.1797)
0.8716 33852 1.3636 - - - - -
0.8736 33930 1.3654 - - - - -
0.8756 34008 1.365 - - - - -
0.8776 34086 1.3769 - - - - -
0.8797 34164 1.3679 - - - - -
0.8814 34232 - 1.3558 0.6891 (+0.1486) 0.4378 (+0.1128) 0.7802 (+0.2796) 0.6357 (+0.1803)
0.8817 34242 1.3614 - - - - -
0.8837 34320 1.3672 - - - - -
0.8857 34398 1.3632 - - - - -
0.8877 34476 1.3759 - - - - -
0.8897 34554 1.3704 - - - - -
0.8914 34621 - 1.3621 0.6851 (+0.1447) 0.4381 (+0.1131) 0.7810 (+0.2804) 0.6348 (+0.1794)
0.8917 34632 1.3523 - - - - -
0.8937 34710 1.3444 - - - - -
0.8957 34788 1.3419 - - - - -
0.8977 34866 1.3616 - - - - -
0.8997 34944 1.3519 - - - - -
0.9014 35010 - 1.3627 0.6878 (+0.1474) 0.4377 (+0.1127) 0.7732 (+0.2726) 0.6329 (+0.1776)
0.9017 35022 1.3614 - - - - -
0.9038 35100 1.3606 - - - - -
0.9058 35178 1.3401 - - - - -
0.9078 35256 1.3503 - - - - -
0.9098 35334 1.3422 - - - - -
0.9115 35399 - 1.3563 0.6938 (+0.1534) 0.4382 (+0.1132) 0.7775 (+0.2768) 0.6365 (+0.1811)
0.9118 35412 1.3397 - - - - -
0.9138 35490 1.3592 - - - - -
0.9158 35568 1.3687 - - - - -
0.9178 35646 1.3452 - - - - -
0.9198 35724 1.3685 - - - - -
0.9215 35788 - 1.3459 0.6877 (+0.1473) 0.4330 (+0.1080) 0.7924 (+0.2917) 0.6377 (+0.1824)
0.9218 35802 1.3542 - - - - -
0.9238 35880 1.3567 - - - - -
0.9258 35958 1.3627 - - - - -
0.9279 36036 1.3476 - - - - -
0.9299 36114 1.3556 - - - - -
0.9315 36177 - 1.3442 0.6951 (+0.1547) 0.4382 (+0.1132) 0.7749 (+0.2742) 0.6361 (+0.1807)
0.9319 36192 1.3444 - - - - -
0.9339 36270 1.3625 - - - - -
0.9359 36348 1.3428 - - - - -
0.9379 36426 1.3575 - - - - -
0.9399 36504 1.3592 - - - - -
0.9415 36566 - 1.3468 0.6848 (+0.1443) 0.4389 (+0.1138) 0.7922 (+0.2916) 0.6386 (+0.1832)
0.9419 36582 1.3317 - - - - -
0.9439 36660 1.3394 - - - - -
0.9459 36738 1.3411 - - - - -
0.9479 36816 1.339 - - - - -
0.9499 36894 1.3346 - - - - -
0.9515 36955 - 1.3424 0.6877 (+0.1473) 0.4382 (+0.1132) 0.7851 (+0.2845) 0.6370 (+0.1816)
0.9520 36972 1.348 - - - - -
0.9540 37050 1.3462 - - - - -
0.9560 37128 1.3339 - - - - -
0.9580 37206 1.3218 - - - - -
0.9600 37284 1.3461 - - - - -
0.9615 37344 - 1.3382 0.6877 (+0.1473) 0.4390 (+0.1139) 0.7851 (+0.2845) 0.6373 (+0.1819)
0.9620 37362 1.3392 - - - - -
0.9640 37440 1.3415 - - - - -
0.9660 37518 1.3423 - - - - -
0.9680 37596 1.3357 - - - - -
0.9700 37674 1.333 - - - - -
0.9715 37733 - 1.3409 0.6877 (+0.1473) 0.4394 (+0.1144) 0.7825 (+0.2819) 0.6366 (+0.1812)
0.9720 37752 1.3111 - - - - -
0.9740 37830 1.3506 - - - - -
0.9761 37908 1.3472 - - - - -
0.9781 37986 1.3273 - - - - -
0.9801 38064 1.337 - - - - -
0.9816 38122 - 1.3355 0.6877 (+0.1473) 0.4383 (+0.1133) 0.7751 (+0.2745) 0.6337 (+0.1784)
0.9821 38142 1.3393 - - - - -
0.9841 38220 1.3205 - - - - -
0.9861 38298 1.3313 - - - - -
0.9881 38376 1.3408 - - - - -
0.9901 38454 1.3463 - - - - -
0.9916 38511 - 1.3325 0.6877 (+0.1473) 0.4366 (+0.1115) 0.7751 (+0.2745) 0.6331 (+0.1778)
0.9921 38532 1.3356 - - - - -
0.9941 38610 1.3352 - - - - -
0.9961 38688 1.3489 - - - - -
0.9981 38766 1.3365 - - - - -
-1 -1 - - 0.7180 (+0.1776) 0.4451 (+0.1201) 0.8011 (+0.3005) 0.6548 (+0.1994)
  • The bold row denotes the saved checkpoint.

Environmental Impact

Carbon emissions were measured using CodeCarbon.

  • Energy Consumed: 24.402 kWh
  • Carbon Emitted: 9.008 kg of CO2
  • Hours Used: 4.849 hours

Training Hardware

  • On Cloud: No
  • GPU Model: 8 x NVIDIA H100 80GB HBM3
  • CPU Model: AMD EPYC 7R13 Processor
  • RAM Size: 1999.99 GB

Framework Versions

  • Python: 3.10.14
  • Sentence Transformers: 5.1.2
  • Transformers: 4.57.1
  • PyTorch: 2.9.1+cu126
  • Accelerate: 1.12.0
  • Datasets: 4.4.1
  • 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",
}

MarginMSELoss 

@misc{hofstätter2021improving,
    title={Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation},
    author={Sebastian Hofstätter and Sophia Althammer and Michael Schröder and Mete Sertkan and Allan Hanbury},
    year={2021},
    eprint={2010.02666},
    archivePrefix={arXiv},
    primaryClass={cs.IR}
}
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