Muennighoff/SBERT-large-nli-v2
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Model: Muennighoff/SBERT-large-nli-v2
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2026-05-13 15:05:45 +08:00
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{
"word_embedding_dimension": 1024,
"pooling_mode_cls_token": false,
"pooling_mode_mean_tokens": true,
"pooling_mode_max_tokens": false,
"pooling_mode_mean_sqrt_len_tokens": false
}

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---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# SBERT-large-nli-v2
## Usage
For usage instructions, refer to our codebase: https://github.com/Muennighoff/sgpt
## Evaluation Results
For eval results, refer to our paper: https://arxiv.org/abs/2202.08904
## Training
The model was trained with the parameters:
**DataLoader**:
`sentence_transformers.datasets.NoDuplicatesDataLoader.NoDuplicatesDataLoader` of length 93941 with parameters:
```
{'batch_size': 6}
```
**Loss**:
`sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss` with parameters:
```
{'scale': 20.0, 'similarity_fct': 'cos_sim'}
```
Parameters of the fit()-Method:
```
{
"epochs": 1,
"evaluation_steps": 9394,
"evaluator": "sentence_transformers.evaluation.EmbeddingSimilarityEvaluator.EmbeddingSimilarityEvaluator",
"max_grad_norm": 1,
"optimizer_class": "<class 'transformers.optimization.AdamW'>",
"optimizer_params": {
"lr": 1e-05
},
"scheduler": "WarmupLinear",
"steps_per_epoch": null,
"warmup_steps": 9395,
"weight_decay": 0.01
}
```
## Full Model Architecture
```
SentenceTransformer(
(0): Transformer({'max_seq_length': 75, 'do_lower_case': False}) with Transformer model: BertModel
(1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
)
```
## Citing & Authors
```bibtex
@article{muennighoff2022sgpt,
title={SGPT: GPT Sentence Embeddings for Semantic Search},
author={Muennighoff, Niklas},
journal={arXiv preprint arXiv:2202.08904},
year={2022}
}
```

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{
"_name_or_path": "bert-large-uncased",
"architectures": [
"BertModel"
],
"attention_probs_dropout_prob": 0.1,
"classifier_dropout": null,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 1024,
"initializer_range": 0.02,
"intermediate_size": 4096,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "bert",
"num_attention_heads": 16,
"num_hidden_layers": 24,
"pad_token_id": 0,
"position_embedding_type": "absolute",
"torch_dtype": "float32",
"transformers_version": "4.11.3",
"type_vocab_size": 2,
"use_cache": true,
"vocab_size": 30522
}

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{
"__version__": {
"sentence_transformers": "2.1.0",
"transformers": "4.11.3",
"pytorch": "1.10.1"
}
}

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0,93940,0.8437320757349038,0.8447999302580305,0.8158973728512129,0.8201478314386461,0.8156840205862232,0.8198638917414217,0.8310484448095099,0.8311148211939917
0,93940,0.8437320757349038,0.8447999302580305,0.8158973728512129,0.8201478314386461,0.8156840205862232,0.8198638917414217,0.8310484448095099,0.8311148211939917
0,93940,0.8437320757349038,0.8447999302580305,0.8158973728512129,0.8201478314386461,0.8156840205862232,0.8198638917414217,0.8310484448095099,0.8311148211939917
0,93940,0.8437320757349038,0.8447999302580305,0.8158973728512129,0.8201478314386461,0.8156840205862232,0.8198638917414217,0.8310484448095099,0.8311148211939917
0,93940,0.8437320757349038,0.8447999302580305,0.8158973728512129,0.8201478314386461,0.8156840205862232,0.8198638917414217,0.8310484448095099,0.8311148211939917
0,93940,0.8437320757349038,0.8447999302580305,0.8158973728512129,0.8201478314386461,0.8156840205862232,0.8198638917414217,0.8310484448095099,0.8311148211939917
0,93940,0.8437320757349038,0.8447999302580305,0.8158973728512129,0.8201478314386461,0.8156840205862232,0.8198638917414217,0.8310484448095099,0.8311148211939917
0,-1,0.8437313128892662,0.8448056900484722,0.815895610345081,0.8201377033177958,0.8156822812149107,0.8198464006261792,0.8310463638823054,0.831102938623535
0,-1,0.8437313128892662,0.8448056900484722,0.815895610345081,0.8201377033177958,0.8156822812149107,0.8198464006261792,0.8310463638823054,0.831102938623535
0,-1,0.8437313128892662,0.8448056900484722,0.815895610345081,0.8201377033177958,0.8156822812149107,0.8198464006261792,0.8310463638823054,0.831102938623535
0,-1,0.8437313128892662,0.8448056900484722,0.815895610345081,0.8201377033177958,0.8156822812149107,0.8198464006261792,0.8310463638823054,0.831102938623535
0,-1,0.8437313128892662,0.8448056900484722,0.815895610345081,0.8201377033177958,0.8156822812149107,0.8198464006261792,0.8310463638823054,0.831102938623535
0,-1,0.8437313128892662,0.8448056900484722,0.815895610345081,0.8201377033177958,0.8156822812149107,0.8198464006261792,0.8310463638823054,0.831102938623535
0,-1,0.8437313128892662,0.8448056900484722,0.815895610345081,0.8201377033177958,0.8156822812149107,0.8198464006261792,0.8310463638823054,0.831102938623535
0,-1,0.8437313128892662,0.8448056900484722,0.815895610345081,0.8201377033177958,0.8156822812149107,0.8198464006261792,0.8310463638823054,0.831102938623535
1 epoch steps cosine_pearson cosine_spearman euclidean_pearson euclidean_spearman manhattan_pearson manhattan_spearman dot_pearson dot_spearman
2 0 9394 0.8490858242089108 0.855820662043251 0.8331457935472963 0.8350664342343017 0.8327844094724506 0.8347379215526596 0.7975655690934436 0.794819326459719
3 0 9394 0.8490858242089108 0.855820662043251 0.8331457935472963 0.8350664342343017 0.8327844094724506 0.8347379215526596 0.7975655690934436 0.794819326459719
4 0 9394 0.8490858242089108 0.855820662043251 0.8331457935472963 0.8350664342343017 0.8327844094724506 0.8347379215526596 0.7975655690934436 0.794819326459719
5 0 9394 0.8490858242089108 0.855820662043251 0.8331457935472963 0.8350664342343017 0.8327844094724506 0.8347379215526596 0.7975655690934436 0.794819326459719
6 0 9394 0.8490858242089108 0.855820662043251 0.8331457935472963 0.8350664342343017 0.8327844094724506 0.8347379215526596 0.7975655690934436 0.794819326459719
7 0 9394 0.8490858242089108 0.855820662043251 0.8331457935472963 0.8350664342343017 0.8327844094724506 0.8347379215526596 0.7975655690934436 0.794819326459719
8 0 9394 0.8490858242089108 0.855820662043251 0.8331457935472963 0.8350664342343017 0.8327844094724506 0.8347379215526596 0.7975655690934436 0.794819326459719
9 0 9394 0.8490858242089108 0.855820662043251 0.8331457935472963 0.8350664342343017 0.8327844094724506 0.8347379215526596 0.7975655690934436 0.794819326459719
10 0 18788 0.8553744290905592 0.8581462828611343 0.8261049159540707 0.8298256626812548 0.8260971451631354 0.8299099990383136 0.8189573669278749 0.8193815604485631
11 0 18788 0.8553744290905592 0.8581462828611343 0.8261049159540707 0.8298256626812548 0.8260971451631354 0.8299099990383136 0.8189573669278749 0.8193815604485631
12 0 18788 0.8553744290905592 0.8581462828611343 0.8261049159540707 0.8298256626812548 0.8260971451631354 0.8299099990383136 0.8189573669278749 0.8193815604485631
13 0 18788 0.8553744290905592 0.8581462828611343 0.8261049159540707 0.8298256626812548 0.8260971451631354 0.8299099990383136 0.8189573669278749 0.8193815604485631
14 0 18788 0.8553744290905592 0.8581462828611343 0.8261049159540707 0.8298256626812548 0.8260971451631354 0.8299099990383136 0.8189573669278749 0.8193815604485631
15 0 18788 0.8553744290905592 0.8581462828611343 0.8261049159540707 0.8298256626812548 0.8260971451631354 0.8299099990383136 0.8189573669278749 0.8193815604485631
16 0 18788 0.8553744290905592 0.8581462828611343 0.8261049159540707 0.8298256626812548 0.8260971451631354 0.8299099990383136 0.8189573669278749 0.8193815604485631
17 0 18788 0.8553744290905592 0.8581462828611343 0.8261049159540707 0.8298256626812548 0.8260971451631354 0.8299099990383136 0.8189573669278749 0.8193815604485631
18 0 28182 0.8504187400172329 0.8529898682797761 0.82704476027472 0.8306843707197624 0.8266952929931073 0.830335758380157 0.8218146242443229 0.821595764819648
19 0 28182 0.8504187400172329 0.8529898682797761 0.82704476027472 0.8306843707197624 0.8266952929931073 0.830335758380157 0.8218146242443229 0.821595764819648
20 0 28182 0.8504187400172329 0.8529898682797761 0.82704476027472 0.8306843707197624 0.8266952929931073 0.830335758380157 0.8218146242443229 0.821595764819648
21 0 28182 0.8504187400172329 0.8529898682797761 0.82704476027472 0.8306843707197624 0.8266952929931073 0.830335758380157 0.8218146242443229 0.821595764819648
22 0 28182 0.8504187400172329 0.8529898682797761 0.82704476027472 0.8306843707197624 0.8266952929931073 0.830335758380157 0.8218146242443229 0.821595764819648
23 0 28182 0.8504187400172329 0.8529898682797761 0.82704476027472 0.8306843707197624 0.8266952929931073 0.830335758380157 0.8218146242443229 0.821595764819648
24 0 28182 0.8504187400172329 0.8529898682797761 0.82704476027472 0.8306843707197624 0.8266952929931073 0.830335758380157 0.8218146242443229 0.821595764819648
25 0 28182 0.8504187400172329 0.8529898682797761 0.82704476027472 0.8306843707197624 0.8266952929931073 0.830335758380157 0.8218146242443229 0.821595764819648
26 0 37576 0.8433756445556863 0.846610200187373 0.8181038256990507 0.8222743275643051 0.8182922086799488 0.8223577511092727 0.8228330091069185 0.8243639820275941
27 0 37576 0.8433756445556863 0.846610200187373 0.8181038256990507 0.8222743275643051 0.8182922086799488 0.8223577511092727 0.8228330091069185 0.8243639820275941
28 0 37576 0.8433756445556863 0.846610200187373 0.8181038256990507 0.8222743275643051 0.8182922086799488 0.8223577511092727 0.8228330091069185 0.8243639820275941
29 0 37576 0.8433756445556863 0.846610200187373 0.8181038256990507 0.8222743275643051 0.8182922086799488 0.8223577511092727 0.8228330091069185 0.8243639820275941
30 0 37576 0.8433756445556863 0.846610200187373 0.8181038256990507 0.8222743275643051 0.8182922086799488 0.8223577511092727 0.8228330091069185 0.8243639820275941
31 0 37576 0.8433756445556863 0.846610200187373 0.8181038256990507 0.8222743275643051 0.8182922086799488 0.8223577511092727 0.8228330091069185 0.8243639820275941
32 0 37576 0.8433756445556863 0.846610200187373 0.8181038256990507 0.8222743275643051 0.8182922086799488 0.8223577511092727 0.8228330091069185 0.8243639820275941
33 0 37576 0.8433756445556863 0.846610200187373 0.8181038256990507 0.8222743275643051 0.8182922086799488 0.8223577511092727 0.8228330091069185 0.8243639820275941
34 0 46970 0.8460147377257901 0.8479995641330417 0.8177865629244383 0.8211161328169037 0.8173821403683041 0.8207322250793376 0.8255372370723681 0.8266552202595329
35 0 46970 0.8460147377257901 0.8479995641330417 0.8177865629244383 0.8211161328169037 0.8173821403683041 0.8207322250793376 0.8255372370723681 0.8266552202595329
36 0 46970 0.8460147377257901 0.8479995641330417 0.8177865629244383 0.8211161328169037 0.8173821403683041 0.8207322250793376 0.8255372370723681 0.8266552202595329
37 0 46970 0.8460147377257901 0.8479995641330417 0.8177865629244383 0.8211161328169037 0.8173821403683041 0.8207322250793376 0.8255372370723681 0.8266552202595329
38 0 46970 0.8460147377257901 0.8479995641330417 0.8177865629244383 0.8211161328169037 0.8173821403683041 0.8207322250793376 0.8255372370723681 0.8266552202595329
39 0 46970 0.8460147377257901 0.8479995641330417 0.8177865629244383 0.8211161328169037 0.8173821403683041 0.8207322250793376 0.8255372370723681 0.8266552202595329
40 0 46970 0.8460147377257901 0.8479995641330417 0.8177865629244383 0.8211161328169037 0.8173821403683041 0.8207322250793376 0.8255372370723681 0.8266552202595329
41 0 46970 0.8460147377257901 0.8479995641330417 0.8177865629244383 0.8211161328169037 0.8173821403683041 0.8207322250793376 0.8255372370723681 0.8266552202595329
42 0 56364 0.8451546145173996 0.8462922960539583 0.8177046022687481 0.8211771522721143 0.8176957176719277 0.8212923454120061 0.8262525595816623 0.8271807544291047
43 0 56364 0.8451546145173996 0.8462922960539583 0.8177046022687481 0.8211771522721143 0.8176957176719277 0.8212923454120061 0.8262525595816623 0.8271807544291047
44 0 56364 0.8451546145173996 0.8462922960539583 0.8177046022687481 0.8211771522721143 0.8176957176719277 0.8212923454120061 0.8262525595816623 0.8271807544291047
45 0 56364 0.8451546145173996 0.8462922960539583 0.8177046022687481 0.8211771522721143 0.8176957176719277 0.8212923454120061 0.8262525595816623 0.8271807544291047
46 0 56364 0.8451546145173996 0.8462922960539583 0.8177046022687481 0.8211771522721143 0.8176957176719277 0.8212923454120061 0.8262525595816623 0.8271807544291047
47 0 56364 0.8451546145173996 0.8462922960539583 0.8177046022687481 0.8211771522721143 0.8176957176719277 0.8212923454120061 0.8262525595816623 0.8271807544291047
48 0 56364 0.8451546145173996 0.8462922960539583 0.8177046022687481 0.8211771522721143 0.8176957176719277 0.8212923454120061 0.8262525595816623 0.8271807544291047
49 0 56364 0.8451546145173996 0.8462922960539583 0.8177046022687481 0.8211771522721143 0.8176957176719277 0.8212923454120061 0.8262525595816623 0.8271807544291047
50 0 65758 0.8433926267974765 0.8448841278248834 0.8162907587417658 0.8202673582113118 0.8159354518040114 0.8201126285674398 0.827943649586429 0.8287123070847461
51 0 65758 0.8433926267974765 0.8448841278248834 0.8162907587417658 0.8202673582113118 0.8159354518040114 0.8201126285674398 0.827943649586429 0.8287123070847461
52 0 65758 0.8433926267974765 0.8448841278248834 0.8162907587417658 0.8202673582113118 0.8159354518040114 0.8201126285674398 0.827943649586429 0.8287123070847461
53 0 65758 0.8433926267974765 0.8448841278248834 0.8162907587417658 0.8202673582113118 0.8159354518040114 0.8201126285674398 0.827943649586429 0.8287123070847461
54 0 65758 0.8433926267974765 0.8448841278248834 0.8162907587417658 0.8202673582113118 0.8159354518040114 0.8201126285674398 0.827943649586429 0.8287123070847461
55 0 65758 0.8433926267974765 0.8448841278248834 0.8162907587417658 0.8202673582113118 0.8159354518040114 0.8201126285674398 0.827943649586429 0.8287123070847461
56 0 65758 0.8433926267974765 0.8448841278248834 0.8162907587417658 0.8202673582113118 0.8159354518040114 0.8201126285674398 0.827943649586429 0.8287123070847461
57 0 65758 0.8433926267974765 0.8448841278248834 0.8162907587417658 0.8202673582113118 0.8159354518040114 0.8201126285674398 0.827943649586429 0.8287123070847461
58 0 75152 0.8446040925038956 0.8448201918378135 0.8156779589594462 0.8197217831026785 0.8153511249507209 0.8195530071857927 0.8310105126796238 0.8314112536317299
59 0 75152 0.8446040925038956 0.8448201918378135 0.8156779589594462 0.8197217831026785 0.8153511249507209 0.8195530071857927 0.8310105126796238 0.8314112536317299
60 0 75152 0.8446040925038956 0.8448201918378135 0.8156779589594462 0.8197217831026785 0.8153511249507209 0.8195530071857927 0.8310105126796238 0.8314112536317299
61 0 75152 0.8446040925038956 0.8448201918378135 0.8156779589594462 0.8197217831026785 0.8153511249507209 0.8195530071857927 0.8310105126796238 0.8314112536317299
62 0 75152 0.8446040925038956 0.8448201918378135 0.8156779589594462 0.8197217831026785 0.8153511249507209 0.8195530071857927 0.8310105126796238 0.8314112536317299
63 0 75152 0.8446040925038956 0.8448201918378135 0.8156779589594462 0.8197217831026785 0.8153511249507209 0.8195530071857927 0.8310105126796238 0.8314112536317299
64 0 75152 0.8446040925038956 0.8448201918378135 0.8156779589594462 0.8197217831026785 0.8153511249507209 0.8195530071857927 0.8310105126796238 0.8314112536317299
65 0 75152 0.8446040925038956 0.8448201918378135 0.8156779589594462 0.8197217831026785 0.8153511249507209 0.8195530071857927 0.8310105126796238 0.8314112536317299
66 0 84546 0.843446814296738 0.8441162411753252 0.8163671546102611 0.8202042389507829 0.8161744627422614 0.8199274120869228 0.8304331386108932 0.8307216323112473
67 0 84546 0.843446814296738 0.8441162411753252 0.8163671546102611 0.8202042389507829 0.8161744627422614 0.8199274120869228 0.8304331386108932 0.8307216323112473
68 0 84546 0.843446814296738 0.8441162411753252 0.8163671546102611 0.8202042389507829 0.8161744627422614 0.8199274120869228 0.8304331386108932 0.8307216323112473
69 0 84546 0.843446814296738 0.8441162411753252 0.8163671546102611 0.8202042389507829 0.8161744627422614 0.8199274120869228 0.8304331386108932 0.8307216323112473
70 0 84546 0.843446814296738 0.8441162411753252 0.8163671546102611 0.8202042389507829 0.8161744627422614 0.8199274120869228 0.8304331386108932 0.8307216323112473
71 0 84546 0.843446814296738 0.8441162411753252 0.8163671546102611 0.8202042389507829 0.8161744627422614 0.8199274120869228 0.8304331386108932 0.8307216323112473
72 0 84546 0.843446814296738 0.8441162411753252 0.8163671546102611 0.8202042389507829 0.8161744627422614 0.8199274120869228 0.8304331386108932 0.8307216323112473
73 0 84546 0.843446814296738 0.8441162411753252 0.8163671546102611 0.8202042389507829 0.8161744627422614 0.8199274120869228 0.8304331386108932 0.8307216323112473
74 0 93940 0.8437320757349038 0.8447999302580305 0.8158973728512129 0.8201478314386461 0.8156840205862232 0.8198638917414217 0.8310484448095099 0.8311148211939917
75 0 93940 0.8437320757349038 0.8447999302580305 0.8158973728512129 0.8201478314386461 0.8156840205862232 0.8198638917414217 0.8310484448095099 0.8311148211939917
76 0 93940 0.8437320757349038 0.8447999302580305 0.8158973728512129 0.8201478314386461 0.8156840205862232 0.8198638917414217 0.8310484448095099 0.8311148211939917
77 0 93940 0.8437320757349038 0.8447999302580305 0.8158973728512129 0.8201478314386461 0.8156840205862232 0.8198638917414217 0.8310484448095099 0.8311148211939917
78 0 93940 0.8437320757349038 0.8447999302580305 0.8158973728512129 0.8201478314386461 0.8156840205862232 0.8198638917414217 0.8310484448095099 0.8311148211939917
79 0 93940 0.8437320757349038 0.8447999302580305 0.8158973728512129 0.8201478314386461 0.8156840205862232 0.8198638917414217 0.8310484448095099 0.8311148211939917
80 0 93940 0.8437320757349038 0.8447999302580305 0.8158973728512129 0.8201478314386461 0.8156840205862232 0.8198638917414217 0.8310484448095099 0.8311148211939917
81 0 93940 0.8437320757349038 0.8447999302580305 0.8158973728512129 0.8201478314386461 0.8156840205862232 0.8198638917414217 0.8310484448095099 0.8311148211939917
82 0 -1 0.8437313128892662 0.8448056900484722 0.815895610345081 0.8201377033177958 0.8156822812149107 0.8198464006261792 0.8310463638823054 0.831102938623535
83 0 -1 0.8437313128892662 0.8448056900484722 0.815895610345081 0.8201377033177958 0.8156822812149107 0.8198464006261792 0.8310463638823054 0.831102938623535
84 0 -1 0.8437313128892662 0.8448056900484722 0.815895610345081 0.8201377033177958 0.8156822812149107 0.8198464006261792 0.8310463638823054 0.831102938623535
85 0 -1 0.8437313128892662 0.8448056900484722 0.815895610345081 0.8201377033177958 0.8156822812149107 0.8198464006261792 0.8310463638823054 0.831102938623535
86 0 -1 0.8437313128892662 0.8448056900484722 0.815895610345081 0.8201377033177958 0.8156822812149107 0.8198464006261792 0.8310463638823054 0.831102938623535
87 0 -1 0.8437313128892662 0.8448056900484722 0.815895610345081 0.8201377033177958 0.8156822812149107 0.8198464006261792 0.8310463638823054 0.831102938623535
88 0 -1 0.8437313128892662 0.8448056900484722 0.815895610345081 0.8201377033177958 0.8156822812149107 0.8198464006261792 0.8310463638823054 0.831102938623535
89 0 -1 0.8437313128892662 0.8448056900484722 0.815895610345081 0.8201377033177958 0.8156822812149107 0.8198464006261792 0.8310463638823054 0.831102938623535

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modules.json Normal file
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}
]

3
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version https://git-lfs.github.com/spec/v1
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4
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{
"max_seq_length": 75,
"do_lower_case": false
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9
similarity_evaluation_sts-test_results.csv Normal file
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epoch,steps,cosine_pearson,cosine_spearman,euclidean_pearson,euclidean_spearman,manhattan_pearson,manhattan_spearman,dot_pearson,dot_spearman
-1,-1,0.8407875970815959,0.841459769408347,0.821371915049623,0.819864434233481,0.8209330570753741,0.8195859084312098,0.7792644877487102,0.7704072139452914
-1,-1,0.8407875970815959,0.841459769408347,0.821371915049623,0.819864434233481,0.8209330570753741,0.8195859084312098,0.7792644877487102,0.7704072139452914
-1,-1,0.8407875970815959,0.841459769408347,0.821371915049623,0.819864434233481,0.8209330570753741,0.8195859084312098,0.7792644877487102,0.7704072139452914
-1,-1,0.8407875970815959,0.841459769408347,0.821371915049623,0.819864434233481,0.8209330570753741,0.8195859084312098,0.7792644877487102,0.7704072139452914
-1,-1,0.8407875970815959,0.841459769408347,0.821371915049623,0.819864434233481,0.8209330570753741,0.8195859084312098,0.7792644877487102,0.7704072139452914
-1,-1,0.8407875970815959,0.841459769408347,0.821371915049623,0.819864434233481,0.8209330570753741,0.8195859084312098,0.7792644877487102,0.7704072139452914
-1,-1,0.8407875970815959,0.841459769408347,0.821371915049623,0.819864434233481,0.8209330570753741,0.8195859084312098,0.7792644877487102,0.7704072139452914
-1,-1,0.8407875970815959,0.841459769408347,0.821371915049623,0.819864434233481,0.8209330570753741,0.8195859084312098,0.7792644877487102,0.7704072139452914
1 epoch steps cosine_pearson cosine_spearman euclidean_pearson euclidean_spearman manhattan_pearson manhattan_spearman dot_pearson dot_spearman
2 -1 -1 0.8407875970815959 0.841459769408347 0.821371915049623 0.819864434233481 0.8209330570753741 0.8195859084312098 0.7792644877487102 0.7704072139452914
3 -1 -1 0.8407875970815959 0.841459769408347 0.821371915049623 0.819864434233481 0.8209330570753741 0.8195859084312098 0.7792644877487102 0.7704072139452914
4 -1 -1 0.8407875970815959 0.841459769408347 0.821371915049623 0.819864434233481 0.8209330570753741 0.8195859084312098 0.7792644877487102 0.7704072139452914
5 -1 -1 0.8407875970815959 0.841459769408347 0.821371915049623 0.819864434233481 0.8209330570753741 0.8195859084312098 0.7792644877487102 0.7704072139452914
6 -1 -1 0.8407875970815959 0.841459769408347 0.821371915049623 0.819864434233481 0.8209330570753741 0.8195859084312098 0.7792644877487102 0.7704072139452914
7 -1 -1 0.8407875970815959 0.841459769408347 0.821371915049623 0.819864434233481 0.8209330570753741 0.8195859084312098 0.7792644877487102 0.7704072139452914
8 -1 -1 0.8407875970815959 0.841459769408347 0.821371915049623 0.819864434233481 0.8209330570753741 0.8195859084312098 0.7792644877487102 0.7704072139452914
9 -1 -1 0.8407875970815959 0.841459769408347 0.821371915049623 0.819864434233481 0.8209330570753741 0.8195859084312098 0.7792644877487102 0.7704072139452914

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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

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{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "bert-large-uncased", "tokenizer_class": "BertTokenizer"}

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