kselight/123BERT

CrossEncoder

This is a Cross Encoder model trained 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
• Maximum Sequence Length: 512 tokens
• Number of Output Labels: 1 label
• Training Dataset:
  • msmarco
• Language: en

Model Sources

• Documentation: Sentence Transformers Documentation
• Documentation: Cross Encoder Documentation
• Repository: Sentence Transformers on GitHub
• Hugging Face: Cross Encoders on Hugging Face

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("kselight/123BERT")
# Get scores for pairs of texts
pairs = [
    ['what is ivana trump', 'The need for an independent investigation. As it stands, all three men in charge of the investigations into the Trump campaign are Republicans, and two of the three are vociferous Trump allies. Burr, the third, also tied himself to Trump during his close 2016 reelection campaign.'],
    ["hogan's goat meaning", 'hoganâ\x80\x99s goat. The phrase like Hoganâ\x80\x99s goat refers to something that is faulty, messed up, or stinks like a goat. The phrase is a reference to R.F. Outcaultâ\x80\x99s seminal newspaper comic Hoganâ\x80\x99s Alley, which debuted in 1895. The title of the strip changed to The Yellow Kid the following year.'],
    ['who made tokyo ghoul', "Tokyo Ghoul (Japanese: æ\x9d±äº¬å\x96°ç¨®ï¼\x88ã\x83\x88ã\x83¼ã\x82\xadã\x83§ã\x83¼ã\x82°ã\x83¼ã\x83«ï¼\x89, Hepburn: TÅ\x8dkyÅ\x8d GÅ«ru) is a Japanese manga series by Sui Ishida. It was serialized in Shueisha's seinen manga magazine Weekly Young Jump between September 2011 and September 2014 and has been collected in fourteen tankÅ\x8dbon volumes as of August 2014."],
    ['neck of the scottie dog', 'Classical guitars. The classical guitar neck blank is relatively small compared to what is needed for construction. This is because a classical neck is constructed differently than most other neck designs. The heel of the neck is built up by stacking blocks of wood to achieve the necessary height.'],
    ['what does bicameral mean in government', 'Top 10 amazing movie makeup transformations. In government, bicameralism is the practice of having two legislative or parliamentary chambers. The relationship between the two chambers of a bicameral legislature can vary. In some cases, they have equal power, and in others, one chamber is clearly superior to the other. It is commonplace in most federal systems to have a bicameral legislature.'],
]
scores = model.predict(pairs)
print(scores.shape)
# (5,)

# Or rank different texts based on similarity to a single text
ranks = model.rank(
    'what is ivana trump',
    [
        'The need for an independent investigation. As it stands, all three men in charge of the investigations into the Trump campaign are Republicans, and two of the three are vociferous Trump allies. Burr, the third, also tied himself to Trump during his close 2016 reelection campaign.',
        'hoganâ\x80\x99s goat. The phrase like Hoganâ\x80\x99s goat refers to something that is faulty, messed up, or stinks like a goat. The phrase is a reference to R.F. Outcaultâ\x80\x99s seminal newspaper comic Hoganâ\x80\x99s Alley, which debuted in 1895. The title of the strip changed to The Yellow Kid the following year.',
        "Tokyo Ghoul (Japanese: æ\x9d±äº¬å\x96°ç¨®ï¼\x88ã\x83\x88ã\x83¼ã\x82\xadã\x83§ã\x83¼ã\x82°ã\x83¼ã\x83«ï¼\x89, Hepburn: TÅ\x8dkyÅ\x8d GÅ«ru) is a Japanese manga series by Sui Ishida. It was serialized in Shueisha's seinen manga magazine Weekly Young Jump between September 2011 and September 2014 and has been collected in fourteen tankÅ\x8dbon volumes as of August 2014.",
        'Classical guitars. The classical guitar neck blank is relatively small compared to what is needed for construction. This is because a classical neck is constructed differently than most other neck designs. The heel of the neck is built up by stacking blocks of wood to achieve the necessary height.',
        'Top 10 amazing movie makeup transformations. In government, bicameralism is the practice of having two legislative or parliamentary chambers. The relationship between the two chambers of a bicameral legislature can vary. In some cases, they have equal power, and in others, one chamber is clearly superior to the other. It is commonplace in most federal systems to have a bicameral legislature.',
    ]
)
# [{'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	0.0579 (-0.4317)	0.2867 (+0.0257)	0.0326 (-0.3870)
mrr@10	0.0329 (-0.4446)	0.4222 (-0.0777)	0.0100 (-0.4167)
ndcg@10	0.0479 (-0.4925)	0.2546 (-0.0705)	0.0229 (-0.4778)

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	0.1257 (-0.2643)
mrr@10	0.1550 (-0.3130)
ndcg@10	0.1084 (-0.3469)

Training Details

Training Dataset

msmarco

• Dataset: msmarco at 9e329ed
• Size: 10,000 training samples
• Columns: score, query, and passage
• Approximate statistics based on the first 1000 samples:

  	score	query	passage
  type	float	string	string
  details	min: -11.79 mean: 0.58 max: 11.1	min: 9 characters mean: 34.21 characters max: 140 characters	min: 70 characters mean: 342.2 characters max: 894 characters

• Samples:

  score	query	passage
  6.720487356185913	modern definition of democracy	Links. A Short Definition of Democracy U.S. president Abraham Lincoln (1809-1865) defined democracy as: «Government of the people, by the people, for the people» Democracy is by far the most challenging form of government-both for politicians and for the people.The term democracy comes from the Greek language and means rule by the (simple) people. The so-called democracies in classical antiquity (Athens and Rome) represent precursors of modern democracies.Like modern democracy, they were created as a reaction to a concentration and abuse of power by the rulers.he term democracy comes from the Greek language and means rule by the (simple) people. The so-called democracies in classical antiquity (Athens and Rome) represent precursors of modern democracies.
  1.6529417037963867	is celexa and fluoxetine same	Celexa (citalopram hydrobromide) is a type of antidepressant called a selective serotonin reuptake inhibitor (SSRI) indicated for the treatment of depression. Celexa is available in generic form. Common side effects of Celexa include. constipation, nausea, diarrhea, upset stomach, decreased sexual desire,
  -9.121654828389486	what are 2 examples of nonpoint pollution	Concept of pollution tax. All such measures are compensatory in nature and it is not called pollution tax. The concept of pollution tax is something different. It entails that instead of doing offsetting work by yourself wherever you hurt environment either willfully or without any intention you have to pay for it.

• Loss: MSELoss with these parameters:

  {
      "activation_fn": "torch.nn.modules.linear.Identity"
  }
  

Evaluation Dataset

msmarco

• Dataset: msmarco at 9e329ed
• Size: 1,000 evaluation samples
• Columns: score, query, and passage
• Approximate statistics based on the first 1000 samples:

  	score	query	passage
  type	float	string	string
  details	min: -11.85 mean: 1.11 max: 11.15	min: 7 characters mean: 34.0 characters max: 186 characters	min: 76 characters mean: 343.66 characters max: 944 characters

• Samples:

  score	query	passage
  -11.078993638356527	what is ivana trump	The need for an independent investigation. As it stands, all three men in charge of the investigations into the Trump campaign are Republicans, and two of the three are vociferous Trump allies. Burr, the third, also tied himself to Trump during his close 2016 reelection campaign.
  8.86651055018107	hogan's goat meaning	hogan’s goat. The phrase like Hogan’s goat refers to something that is faulty, messed up, or stinks like a goat. The phrase is a reference to R.F. Outcault’s seminal newspaper comic Hogan’s Alley, which debuted in 1895. The title of the strip changed to The Yellow Kid the following year.
  8.381712992986044	who made tokyo ghoul	Tokyo Ghoul (Japanese: 東京喰種（トーキョーグール）, Hepburn: Tōkyō Gūru) is a Japanese manga series by Sui Ishida. It was serialized in Shueisha's seinen manga magazine Weekly Young Jump between September 2011 and September 2014 and has been collected in fourteen tankōbon volumes as of August 2014.

• Loss: MSELoss with these parameters:

  {
      "activation_fn": "torch.nn.modules.linear.Identity"
  }
  

Training Hyperparameters

Non-Default Hyperparameters

• eval_strategy: steps
• per_device_train_batch_size: 16
• per_device_eval_batch_size: 16
• learning_rate: 8e-06
• num_train_epochs: 1
• warmup_ratio: 0.1
• seed: 12
• dataloader_num_workers: 4
• 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: 16
• per_device_eval_batch_size: 16
• per_gpu_train_batch_size: None
• per_gpu_eval_batch_size: None
• gradient_accumulation_steps: 1
• eval_accumulation_steps: None
• torch_empty_cache_steps: None
• learning_rate: 8e-06
• weight_decay: 0.0
• adam_beta1: 0.9
• adam_beta2: 0.999
• adam_epsilon: 1e-08
• max_grad_norm: 1.0
• num_train_epochs: 1
• max_steps: -1
• lr_scheduler_type: linear
• lr_scheduler_kwargs: {}
• warmup_ratio: 0.1
• warmup_steps: 0
• log_level: passive
• log_level_replica: warning
• log_on_each_node: True
• logging_nan_inf_filter: True
• save_safetensors: True
• save_on_each_node: False
• save_only_model: False
• restore_callback_states_from_checkpoint: False
• no_cuda: False
• use_cpu: False
• use_mps_device: False
• seed: 12
• data_seed: None
• jit_mode_eval: False
• use_ipex: False
• bf16: 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: 4
• 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}
• deepspeed: None
• label_smoothing_factor: 0.0
• optim: adamw_torch
• optim_args: None
• adafactor: False
• group_by_length: False
• length_column_name: length
• ddp_find_unused_parameters: None
• ddp_bucket_cap_mb: None
• ddp_broadcast_buffers: False
• dataloader_pin_memory: True
• dataloader_persistent_workers: False
• skip_memory_metrics: True
• use_legacy_prediction_loop: False
• push_to_hub: False
• resume_from_checkpoint: None
• hub_model_id: None
• hub_strategy: every_save
• hub_private_repo: None
• hub_always_push: False
• gradient_checkpointing: False
• gradient_checkpointing_kwargs: None
• include_inputs_for_metrics: False
• include_for_metrics: []
• eval_do_concat_batches: True
• fp16_backend: auto
• push_to_hub_model_id: None
• push_to_hub_organization: None
• mp_parameters:
• auto_find_batch_size: False
• full_determinism: False
• torchdynamo: None
• ray_scope: last
• ddp_timeout: 1800
• torch_compile: False
• torch_compile_backend: None
• torch_compile_mode: None
• 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
• use_liger_kernel: False
• eval_use_gather_object: False
• average_tokens_across_devices: False
• prompts: None
• batch_sampler: batch_sampler
• multi_dataset_batch_sampler: proportional
• router_mapping: {}
• learning_rate_mapping: {}

Training Logs

Epoch	Step	Training Loss	NanoMSMARCO_R100_ndcg@10	NanoNFCorpus_R100_ndcg@10	NanoNQ_R100_ndcg@10	NanoBEIR_R100_mean_ndcg@10
-1	-1	-	0.0479 (-0.4925)	0.2546 (-0.0705)	0.0229 (-0.4778)	0.1084 (-0.3469)
0.0064	1	53.6175	-	-	-	-

Framework Versions

• Python: 3.11.6
• Sentence Transformers: 5.1.1
• Transformers: 4.47.1
• PyTorch: 2.4.0+cu124
• Accelerate: 1.5.1
• Datasets: 3.3.2
• Tokenizers: 0.21.1

Citation

BibTeX

Sentence Transformers

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}