This is a Cross Encoder model finetuned from BAAI/bge-reranker-v2-m3 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: BAAI/bge-reranker-v2-m3
Maximum Sequence Length: 512 tokens
Number of Output Labels: 1 label

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.

python

from sentence_transformers import CrossEncoder

# Download from the 🤗 Hub
model = CrossEncoder("steerrec/bge-reranker-v2-m3-amazon")
# Get scores for pairs of texts
pairs = [
    ["I want something emotional and heartfelt, but not boring. I don't want another slow, dull show.", 'Civil Love Product description Civil Love Review Every so often you come across a movie you really enjoy. For me, this was it. This film contains everything a good movie needs: a good story, fine acting, direction, and a purpose. The theme of this film is that we are too quick to judge people sometimes and that people can occasionally surprise us. --Edwin L. Carpenter, Dove Foundation Movies & TV Genre for Featured Categories Drama'],
    ["I want something emotional and heartfelt, but not boring. I don't want another slow, dull show.", 'Surprised by Love A young businesswoman tries to convince her uptight parents to accept her boyfriend, but then she falls for an old high-school flame. Stars Hilarie Burton, Paul Campbell, and Tim Conway. IMDb 6.7 1 h 24 min 2015 7+ Drama Cheerful Passionate'],
    ["I want something emotional and heartfelt, but not boring. I don't want another slow, dull show.", 'All I Want for Christmas Tis the season for making dreams true. If everything goes according to plan for one young boy, he just may be sharing this Christmas with a new dad. Ever since her husband died, Sarah Armstrong has divided her time between working at a community center and caring for her nine-year-old son, Jesse. When Jesse wins the All I Want for Christmas contest sponsored by a toy company, his wish comes as no surprise to find a new dad. Just in time for the holidays, All I Want for Christmas is a surprise romantic treat for anyone who believes in the magic of love, friendship, and family. Movies & TV Holidays & Seasonal Christmas'],
    ["I just finished a few really touching movies and shows that left me feeling deeply moved and emotionally invested. I'm now looking for something that keeps that same heartfelt, character-driven vibe but with a bit more depth and complexity. I want to watch something that's a mix of drama and drama, maybe with some drama or drama, but it's hard to say. I'm looking for something that combines the elements of a story, a character, and the setting of the characters. It's like a movie where the plot is driven by the people involved, not just the events. I'm craving something that's not too fast-paced, but still has enough substance to keep me engaged. Maybe something that's a little more complex than your average film, but not so much that it feels overwhelming. I'm also interested in something that's not too dark, but still has some emotional weight. I want to feel connected to the characters and their journeys, even if they're not the most straightforward. I'm in the mood for something that's a bit more than just a movie. I need something that's a bit more intricate, with a strong narrative that's not just about the characters but the world they inhabit. I'm looking for a show that's not just a collection of characters but a full, immersive experience. I'm not sure what exactly I", "The Guardian Action-packed drama that takes you inside the never-before-seen world of the elite Coast Guard Rescue Swimmers. Reeling with grief from a mission gone tragically wrong, a legendary swimmer is given a mission he doesn't want -- training raw recruits. IMDb 6.9 2 h 19 min 2006 X-Ray PG-13 Drama Adventure Compelling Inspiring"],
    ["I just finished a few really touching movies and shows that left me feeling deeply moved and emotionally invested. I'm now looking for something that keeps that same heartfelt, character-driven vibe but with a bit more depth and complexity. I want to watch something that's a mix of drama and drama, maybe with some drama or drama, but it's hard to say. I'm looking for something that combines the elements of a story, a character, and the setting of the characters. It's like a movie where the plot is driven by the people involved, not just the events. I'm craving something that's not too fast-paced, but still has enough substance to keep me engaged. Maybe something that's a little more complex than your average film, but not so much that it feels overwhelming. I'm also interested in something that's not too dark, but still has some emotional weight. I want to feel connected to the characters and their journeys, even if they're not the most straightforward. I'm in the mood for something that's a bit more than just a movie. I need something that's a bit more intricate, with a strong narrative that's not just about the characters but the world they inhabit. I'm looking for a show that's not just a collection of characters but a full, immersive experience. I'm not sure what exactly I", 'Magnolia [VHS] An intriguing and entertaining study in characters going through varying levels of crisis and introspection. This psychological drama leads you in several different directions, weaving and intersecting various subplots and characters, from a brilliant Tom Cruise, as a self-proclaimed pied-piper, to a child forced to go on a TV game show and the pressures he faces from a ruthless father. Movies & TV Genre for Featured Categories Drama'],
]
scores = model.predict(pairs)
print(scores.shape)
# (5,)

# Or rank different texts based on similarity to a single text
ranks = model.rank(
    "I want something emotional and heartfelt, but not boring. I don't want another slow, dull show.",
    [
        'Civil Love Product description Civil Love Review Every so often you come across a movie you really enjoy. For me, this was it. This film contains everything a good movie needs: a good story, fine acting, direction, and a purpose. The theme of this film is that we are too quick to judge people sometimes and that people can occasionally surprise us. --Edwin L. Carpenter, Dove Foundation Movies & TV Genre for Featured Categories Drama',
        'Surprised by Love A young businesswoman tries to convince her uptight parents to accept her boyfriend, but then she falls for an old high-school flame. Stars Hilarie Burton, Paul Campbell, and Tim Conway. IMDb 6.7 1 h 24 min 2015 7+ Drama Cheerful Passionate',
        'All I Want for Christmas Tis the season for making dreams true. If everything goes according to plan for one young boy, he just may be sharing this Christmas with a new dad. Ever since her husband died, Sarah Armstrong has divided her time between working at a community center and caring for her nine-year-old son, Jesse. When Jesse wins the All I Want for Christmas contest sponsored by a toy company, his wish comes as no surprise to find a new dad. Just in time for the holidays, All I Want for Christmas is a surprise romantic treat for anyone who believes in the magic of love, friendship, and family. Movies & TV Holidays & Seasonal Christmas',
        "The Guardian Action-packed drama that takes you inside the never-before-seen world of the elite Coast Guard Rescue Swimmers. Reeling with grief from a mission gone tragically wrong, a legendary swimmer is given a mission he doesn't want -- training raw recruits. IMDb 6.9 2 h 19 min 2006 X-Ray PG-13 Drama Adventure Compelling Inspiring",
        'Magnolia [VHS] An intriguing and entertaining study in characters going through varying levels of crisis and introspection. This psychological drama leads you in several different directions, weaving and intersecting various subplots and characters, from a brilliant Tom Cruise, as a self-proclaimed pied-piper, to a child forced to go on a TV game show and the pressures he faces from a ruthless father. Movies & TV Genre for Featured Categories Drama',
    ]
)
# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]

Evaluation

Metrics

Cross Encoder Reranking

Datasets: amazon_test and amazon_val
Evaluated with CrossEncoderRerankingEvaluator with these parameters:
json
1{ 2 "at_k": 10 3}

Metric	amazon_test	amazon_val
map	0.8518	0.8329
mrr@10	0.8888	0.8814
ndcg@10	0.9086	0.9007

Training Details

Training Dataset

Unnamed Dataset

Size: 320,937 training samples
Columns: sentence1, sentence2, and label

Approximate statistics based on the first 1000 samples:

	sentence1	sentence2	label
type	string	string	float
details	min: 78 characters mean: 537.26 characters max: 1341 characters	min: 48 characters mean: 1079.61 characters max: 10645 characters	min: 0.0 mean: 0.33 max: 1.0

Samples:

sentence1	sentence2	label
`I want something emotional and heartfelt, but not boring. I don't want another slow, dull show.`	`Civil Love Product description Civil Love Review Every so often you come across a movie you really enjoy. For me, this was it. This film contains everything a good movie needs: a good story, fine acting, direction, and a purpose. The theme of this film is that we are too quick to judge people sometimes and that people can occasionally surprise us. --Edwin L. Carpenter, Dove Foundation Movies & TV Genre for Featured Categories Drama`	`0.0`
`I want something emotional and heartfelt, but not boring. I don't want another slow, dull show.`	`Surprised by Love A young businesswoman tries to convince her uptight parents to accept her boyfriend, but then she falls for an old high-school flame. Stars Hilarie Burton, Paul Campbell, and Tim Conway. IMDb 6.7 1 h 24 min 2015 7+ Drama Cheerful Passionate`	`0.0`
`I want something emotional and heartfelt, but not boring. I don't want another slow, dull show.`	All I Want for Christmas Tis the season for making dreams true. If everything goes according to plan for one young boy, he just may be sharing this Christmas with a new dad. Ever since her husband died, Sarah Armstrong has divided her time between working at a community center and caring for her nine-year-old son, Jesse. When Jesse wins the All I Want for Christmas contest sponsored by a toy company, his wish comes as no surprise to find a new dad. Just in time for the holidays, All I Want for Christmas is a surprise romantic treat for anyone who believes in the magic of love, friendship, and family. Movies & TV Holidays & Seasonal Christmas	`0.0`

Loss: BinaryCrossEntropyLoss with these parameters:
json
1{ 2 "activation_fn": "torch.nn.modules.linear.Identity", 3 "pos_weight": null 4}

Training Hyperparameters

Non-Default Hyperparameters

eval_strategy: epoch
per_device_train_batch_size: 32
learning_rate: 0.0001
weight_decay: 0.01
num_train_epochs: 1
lr_scheduler_type: cosine
warmup_ratio: 0.05
seed: 3407
bf16: True

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: epoch
prediction_loss_only: True
per_device_train_batch_size: 32
per_device_eval_batch_size: 8
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: 0.0001
weight_decay: 0.01
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: cosine
lr_scheduler_kwargs: {}
warmup_ratio: 0.05
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: 3407
data_seed: None
jit_mode_eval: False
use_ipex: 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: 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}
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
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: False
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: False
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	amazon_test_ndcg@10	amazon_val_ndcg@10
-1	-1	-	0.6715	-
0.0050	50	1.8011	-	-
0.0100	100	0.8447	-	-
0.0150	150	0.6551	-	-
0.0199	200	0.6045	-	-
0.0249	250	0.5639	-	-
0.0299	300	0.5355	-	-
0.0349	350	0.5021	-	-
0.0399	400	0.5279	-	-
0.0449	450	0.4843	-	-
0.0499	500	0.4735	-	-
0.0548	550	0.4647	-	-
0.0598	600	0.4738	-	-
0.0648	650	0.4657	-	-
0.0698	700	0.4873	-	-
0.0748	750	0.4611	-	-
0.0798	800	0.439	-	-
0.0847	850	0.4302	-	-
0.0897	900	0.4417	-	-
0.0947	950	0.4461	-	-
0.0997	1000	0.4277	-	-
0.1047	1050	0.4367	-	-
0.1097	1100	0.4273	-	-
0.1147	1150	0.4104	-	-
0.1196	1200	0.4259	-	-
0.1246	1250	0.4412	-	-
0.1296	1300	0.4075	-	-
0.1346	1350	0.4307	-	-
0.1396	1400	0.4473	-	-
0.1446	1450	0.4502	-	-
0.1496	1500	0.4168	-	-
0.1545	1550	0.4174	-	-
0.1595	1600	0.4229	-	-
0.1645	1650	0.4276	-	-
0.1695	1700	0.4152	-	-
0.1745	1750	0.4236	-	-
0.1795	1800	0.3981	-	-
0.1844	1850	0.4082	-	-
0.1894	1900	0.4261	-	-
0.1944	1950	0.3888	-	-
0.1994	2000	0.4314	-	-
0.2044	2050	0.4254	-	-
0.2094	2100	0.4296	-	-
0.2144	2150	0.4324	-	-
0.2193	2200	0.4074	-	-
0.2243	2250	0.4127	-	-
0.2293	2300	0.4206	-	-
0.2343	2350	0.4078	-	-
0.2393	2400	0.4015	-	-
0.2443	2450	0.4316	-	-
0.2493	2500	0.4067	-	-
0.2542	2550	0.4066	-	-
0.2592	2600	0.3945	-	-
0.2642	2650	0.3927	-	-
0.2692	2700	0.4264	-	-
0.2742	2750	0.3822	-	-
0.2792	2800	0.4176	-	-
0.2841	2850	0.4128	-	-
0.2891	2900	0.3914	-	-
0.2941	2950	0.4091	-	-
0.2991	3000	0.3949	-	-
0.3041	3050	0.407	-	-
0.3091	3100	0.3848	-	-
0.3141	3150	0.4007	-	-
0.3190	3200	0.4089	-	-
0.3240	3250	0.3995	-	-
0.3290	3300	0.3811	-	-
0.3340	3350	0.3821	-	-
0.3390	3400	0.3891	-	-
0.3440	3450	0.3952	-	-
0.3490	3500	0.4013	-	-
0.3539	3550	0.4033	-	-
0.3589	3600	0.3738	-	-
0.3639	3650	0.3887	-	-
0.3689	3700	0.3882	-	-
0.3739	3750	0.3929	-	-
0.3789	3800	0.3858	-	-
0.3838	3850	0.3932	-	-
0.3888	3900	0.3953	-	-
0.3938	3950	0.393	-	-
0.3988	4000	0.3937	-	-
0.4038	4050	0.4102	-	-
0.4088	4100	0.4216	-	-
0.4138	4150	0.3825	-	-
0.4187	4200	0.3997	-	-
0.4237	4250	0.401	-	-
0.4287	4300	0.3984	-	-
0.4337	4350	0.4041	-	-
0.4387	4400	0.388	-	-
0.4437	4450	0.3947	-	-
0.4487	4500	0.3988	-	-
0.4536	4550	0.3826	-	-
0.4586	4600	0.3981	-	-
0.4636	4650	0.4018	-	-
0.4686	4700	0.3696	-	-
0.4736	4750	0.3739	-	-
0.4786	4800	0.397	-	-
0.4835	4850	0.4046	-	-
0.4885	4900	0.3774	-	-
0.4935	4950	0.3795	-	-
0.4985	5000	0.3897	-	-
0.5035	5050	0.3929	-	-
0.5085	5100	0.3783	-	-
0.5135	5150	0.389	-	-
0.5184	5200	0.3832	-	-
0.5234	5250	0.3477	-	-
0.5284	5300	0.3694	-	-
0.5334	5350	0.4011	-	-
0.5384	5400	0.3978	-	-
0.5434	5450	0.3776	-	-
0.5484	5500	0.3939	-	-
0.5533	5550	0.3656	-	-
0.5583	5600	0.3815	-	-
0.5633	5650	0.3664	-	-
0.5683	5700	0.4057	-	-
0.5733	5750	0.3859	-	-
0.5783	5800	0.4032	-	-
0.5833	5850	0.3853	-	-
0.5882	5900	0.3679	-	-
0.5932	5950	0.3748	-	-
0.5982	6000	0.3839	-	-
0.6032	6050	0.3719	-	-
0.6082	6100	0.3626	-	-
0.6132	6150	0.3991	-	-
0.6181	6200	0.3927	-	-
0.6231	6250	0.3923	-	-
0.6281	6300	0.3649	-	-
0.6331	6350	0.3843	-	-
0.6381	6400	0.4072	-	-
0.6431	6450	0.3875	-	-
0.6481	6500	0.3903	-	-
0.6530	6550	0.3658	-	-
0.6580	6600	0.3889	-	-
0.6630	6650	0.3823	-	-
0.6680	6700	0.3789	-	-
0.6730	6750	0.3623	-	-
0.6780	6800	0.3865	-	-
0.6830	6850	0.3809	-	-
0.6879	6900	0.3833	-	-
0.6929	6950	0.3752	-	-
0.6979	7000	0.3834	-	-
0.7029	7050	0.3667	-	-
0.7079	7100	0.3791	-	-
0.7129	7150	0.3689	-	-
0.7178	7200	0.3663	-	-
0.7228	7250	0.3995	-	-
0.7278	7300	0.3696	-	-
0.7328	7350	0.3747	-	-
0.7378	7400	0.377	-	-
0.7428	7450	0.3669	-	-
0.7478	7500	0.3865	-	-
0.7527	7550	0.3757	-	-
0.7577	7600	0.3715	-	-
0.7627	7650	0.3699	-	-
0.7677	7700	0.363	-	-
0.7727	7750	0.3861	-	-
0.7777	7800	0.3518	-	-
0.7827	7850	0.3801	-	-
0.7876	7900	0.3881	-	-
0.7926	7950	0.3797	-	-
0.7976	8000	0.3788	-	-
0.8026	8050	0.3761	-	-
0.8076	8100	0.3838	-	-
0.8126	8150	0.3664	-	-
0.8175	8200	0.3745	-	-
0.8225	8250	0.3706	-	-
0.8275	8300	0.3771	-	-
0.8325	8350	0.3865	-	-
0.8375	8400	0.3601	-	-
0.8425	8450	0.366	-	-
0.8475	8500	0.3651	-	-
0.8524	8550	0.366	-	-
0.8574	8600	0.3676	-	-
0.8624	8650	0.3828	-	-
0.8674	8700	0.3374	-	-
0.8724	8750	0.3644	-	-
0.8774	8800	0.385	-	-
0.8824	8850	0.3678	-	-
0.8873	8900	0.3754	-	-
0.8923	8950	0.3715	-	-
0.8973	9000	0.3889	-	-
0.9023	9050	0.367	-	-
0.9073	9100	0.378	-	-
0.9123	9150	0.3773	-	-
0.9172	9200	0.388	-	-
0.9222	9250	0.3549	-	-
0.9272	9300	0.3726	-	-
0.9322	9350	0.3787	-	-
0.9372	9400	0.3863	-	-
0.9422	9450	0.3705	-	-
0.9472	9500	0.3643	-	-
0.9521	9550	0.4003	-	-
0.9571	9600	0.388	-	-
0.9621	9650	0.3612	-	-
0.9671	9700	0.3664	-	-
0.9721	9750	0.3657	-	-
0.9771	9800	0.3854	-	-
0.9821	9850	0.3544	-	-
0.9870	9900	0.3771	-	-
0.9920	9950	0.3517	-	-
0.9970	10000	0.3659	-	-
1.0	10030	-	-	0.9007
-1	-1	-	0.9086	-

Framework Versions

Python: 3.12.3
Sentence Transformers: 5.3.0
Transformers: 4.56.2
PyTorch: 2.11.0+cu128
Accelerate: 1.13.0
Datasets: 4.3.0
Tokenizers: 0.22.2

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",
}