初始化项目，由ModelHub XC社区提供模型

Model: Muennighoff/SBERT-large-nli-v2
Source: Original Platform

.gitattributes

@@ -0,0 +1,27 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text 
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

1_Pooling/config.json

@@ -0,0 +1,7 @@
+{
+  "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
+}

README.md

@@ -0,0 +1,74 @@
+---
+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}
+}
+```

config.json

@@ -0,0 +1,26 @@
+{
+  "_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
+}

config_sentence_transformers.json

@@ -0,0 +1,7 @@
+{
+  "__version__": {
+    "sentence_transformers": "2.1.0",
+    "transformers": "4.11.3",
+    "pytorch": "1.10.1"
+  }
+}

eval/similarity_evaluation_sts-dev_results.csv

@@ -0,0 +1,89 @@
+epoch,steps,cosine_pearson,cosine_spearman,euclidean_pearson,euclidean_spearman,manhattan_pearson,manhattan_spearman,dot_pearson,dot_spearman
+0,9394,0.8490858242089108,0.855820662043251,0.8331457935472963,0.8350664342343017,0.8327844094724506,0.8347379215526596,0.7975655690934436,0.794819326459719
+0,9394,0.8490858242089108,0.855820662043251,0.8331457935472963,0.8350664342343017,0.8327844094724506,0.8347379215526596,0.7975655690934436,0.794819326459719
+0,9394,0.8490858242089108,0.855820662043251,0.8331457935472963,0.8350664342343017,0.8327844094724506,0.8347379215526596,0.7975655690934436,0.794819326459719
+0,9394,0.8490858242089108,0.855820662043251,0.8331457935472963,0.8350664342343017,0.8327844094724506,0.8347379215526596,0.7975655690934436,0.794819326459719
+0,9394,0.8490858242089108,0.855820662043251,0.8331457935472963,0.8350664342343017,0.8327844094724506,0.8347379215526596,0.7975655690934436,0.794819326459719
+0,9394,0.8490858242089108,0.855820662043251,0.8331457935472963,0.8350664342343017,0.8327844094724506,0.8347379215526596,0.7975655690934436,0.794819326459719
+0,9394,0.8490858242089108,0.855820662043251,0.8331457935472963,0.8350664342343017,0.8327844094724506,0.8347379215526596,0.7975655690934436,0.794819326459719
+0,9394,0.8490858242089108,0.855820662043251,0.8331457935472963,0.8350664342343017,0.8327844094724506,0.8347379215526596,0.7975655690934436,0.794819326459719
+0,18788,0.8553744290905592,0.8581462828611343,0.8261049159540707,0.8298256626812548,0.8260971451631354,0.8299099990383136,0.8189573669278749,0.8193815604485631
+0,18788,0.8553744290905592,0.8581462828611343,0.8261049159540707,0.8298256626812548,0.8260971451631354,0.8299099990383136,0.8189573669278749,0.8193815604485631
+0,18788,0.8553744290905592,0.8581462828611343,0.8261049159540707,0.8298256626812548,0.8260971451631354,0.8299099990383136,0.8189573669278749,0.8193815604485631
+0,18788,0.8553744290905592,0.8581462828611343,0.8261049159540707,0.8298256626812548,0.8260971451631354,0.8299099990383136,0.8189573669278749,0.8193815604485631
+0,18788,0.8553744290905592,0.8581462828611343,0.8261049159540707,0.8298256626812548,0.8260971451631354,0.8299099990383136,0.8189573669278749,0.8193815604485631
+0,18788,0.8553744290905592,0.8581462828611343,0.8261049159540707,0.8298256626812548,0.8260971451631354,0.8299099990383136,0.8189573669278749,0.8193815604485631
+0,18788,0.8553744290905592,0.8581462828611343,0.8261049159540707,0.8298256626812548,0.8260971451631354,0.8299099990383136,0.8189573669278749,0.8193815604485631
+0,18788,0.8553744290905592,0.8581462828611343,0.8261049159540707,0.8298256626812548,0.8260971451631354,0.8299099990383136,0.8189573669278749,0.8193815604485631
+0,28182,0.8504187400172329,0.8529898682797761,0.82704476027472,0.8306843707197624,0.8266952929931073,0.830335758380157,0.8218146242443229,0.821595764819648
+0,28182,0.8504187400172329,0.8529898682797761,0.82704476027472,0.8306843707197624,0.8266952929931073,0.830335758380157,0.8218146242443229,0.821595764819648
+0,28182,0.8504187400172329,0.8529898682797761,0.82704476027472,0.8306843707197624,0.8266952929931073,0.830335758380157,0.8218146242443229,0.821595764819648
+0,28182,0.8504187400172329,0.8529898682797761,0.82704476027472,0.8306843707197624,0.8266952929931073,0.830335758380157,0.8218146242443229,0.821595764819648
+0,28182,0.8504187400172329,0.8529898682797761,0.82704476027472,0.8306843707197624,0.8266952929931073,0.830335758380157,0.8218146242443229,0.821595764819648
+0,28182,0.8504187400172329,0.8529898682797761,0.82704476027472,0.8306843707197624,0.8266952929931073,0.830335758380157,0.8218146242443229,0.821595764819648
+0,28182,0.8504187400172329,0.8529898682797761,0.82704476027472,0.8306843707197624,0.8266952929931073,0.830335758380157,0.8218146242443229,0.821595764819648
+0,28182,0.8504187400172329,0.8529898682797761,0.82704476027472,0.8306843707197624,0.8266952929931073,0.830335758380157,0.8218146242443229,0.821595764819648
+0,37576,0.8433756445556863,0.846610200187373,0.8181038256990507,0.8222743275643051,0.8182922086799488,0.8223577511092727,0.8228330091069185,0.8243639820275941
+0,37576,0.8433756445556863,0.846610200187373,0.8181038256990507,0.8222743275643051,0.8182922086799488,0.8223577511092727,0.8228330091069185,0.8243639820275941
+0,37576,0.8433756445556863,0.846610200187373,0.8181038256990507,0.8222743275643051,0.8182922086799488,0.8223577511092727,0.8228330091069185,0.8243639820275941
+0,37576,0.8433756445556863,0.846610200187373,0.8181038256990507,0.8222743275643051,0.8182922086799488,0.8223577511092727,0.8228330091069185,0.8243639820275941
+0,37576,0.8433756445556863,0.846610200187373,0.8181038256990507,0.8222743275643051,0.8182922086799488,0.8223577511092727,0.8228330091069185,0.8243639820275941
+0,37576,0.8433756445556863,0.846610200187373,0.8181038256990507,0.8222743275643051,0.8182922086799488,0.8223577511092727,0.8228330091069185,0.8243639820275941
+0,37576,0.8433756445556863,0.846610200187373,0.8181038256990507,0.8222743275643051,0.8182922086799488,0.8223577511092727,0.8228330091069185,0.8243639820275941
+0,37576,0.8433756445556863,0.846610200187373,0.8181038256990507,0.8222743275643051,0.8182922086799488,0.8223577511092727,0.8228330091069185,0.8243639820275941
+0,46970,0.8460147377257901,0.8479995641330417,0.8177865629244383,0.8211161328169037,0.8173821403683041,0.8207322250793376,0.8255372370723681,0.8266552202595329
+0,46970,0.8460147377257901,0.8479995641330417,0.8177865629244383,0.8211161328169037,0.8173821403683041,0.8207322250793376,0.8255372370723681,0.8266552202595329
+0,46970,0.8460147377257901,0.8479995641330417,0.8177865629244383,0.8211161328169037,0.8173821403683041,0.8207322250793376,0.8255372370723681,0.8266552202595329
+0,46970,0.8460147377257901,0.8479995641330417,0.8177865629244383,0.8211161328169037,0.8173821403683041,0.8207322250793376,0.8255372370723681,0.8266552202595329
+0,46970,0.8460147377257901,0.8479995641330417,0.8177865629244383,0.8211161328169037,0.8173821403683041,0.8207322250793376,0.8255372370723681,0.8266552202595329
+0,46970,0.8460147377257901,0.8479995641330417,0.8177865629244383,0.8211161328169037,0.8173821403683041,0.8207322250793376,0.8255372370723681,0.8266552202595329
+0,46970,0.8460147377257901,0.8479995641330417,0.8177865629244383,0.8211161328169037,0.8173821403683041,0.8207322250793376,0.8255372370723681,0.8266552202595329
+0,46970,0.8460147377257901,0.8479995641330417,0.8177865629244383,0.8211161328169037,0.8173821403683041,0.8207322250793376,0.8255372370723681,0.8266552202595329
+0,56364,0.8451546145173996,0.8462922960539583,0.8177046022687481,0.8211771522721143,0.8176957176719277,0.8212923454120061,0.8262525595816623,0.8271807544291047
+0,56364,0.8451546145173996,0.8462922960539583,0.8177046022687481,0.8211771522721143,0.8176957176719277,0.8212923454120061,0.8262525595816623,0.8271807544291047
+0,56364,0.8451546145173996,0.8462922960539583,0.8177046022687481,0.8211771522721143,0.8176957176719277,0.8212923454120061,0.8262525595816623,0.8271807544291047
+0,56364,0.8451546145173996,0.8462922960539583,0.8177046022687481,0.8211771522721143,0.8176957176719277,0.8212923454120061,0.8262525595816623,0.8271807544291047
+0,56364,0.8451546145173996,0.8462922960539583,0.8177046022687481,0.8211771522721143,0.8176957176719277,0.8212923454120061,0.8262525595816623,0.8271807544291047
+0,56364,0.8451546145173996,0.8462922960539583,0.8177046022687481,0.8211771522721143,0.8176957176719277,0.8212923454120061,0.8262525595816623,0.8271807544291047
+0,56364,0.8451546145173996,0.8462922960539583,0.8177046022687481,0.8211771522721143,0.8176957176719277,0.8212923454120061,0.8262525595816623,0.8271807544291047
+0,56364,0.8451546145173996,0.8462922960539583,0.8177046022687481,0.8211771522721143,0.8176957176719277,0.8212923454120061,0.8262525595816623,0.8271807544291047
+0,65758,0.8433926267974765,0.8448841278248834,0.8162907587417658,0.8202673582113118,0.8159354518040114,0.8201126285674398,0.827943649586429,0.8287123070847461
+0,65758,0.8433926267974765,0.8448841278248834,0.8162907587417658,0.8202673582113118,0.8159354518040114,0.8201126285674398,0.827943649586429,0.8287123070847461
+0,65758,0.8433926267974765,0.8448841278248834,0.8162907587417658,0.8202673582113118,0.8159354518040114,0.8201126285674398,0.827943649586429,0.8287123070847461
+0,65758,0.8433926267974765,0.8448841278248834,0.8162907587417658,0.8202673582113118,0.8159354518040114,0.8201126285674398,0.827943649586429,0.8287123070847461
+0,65758,0.8433926267974765,0.8448841278248834,0.8162907587417658,0.8202673582113118,0.8159354518040114,0.8201126285674398,0.827943649586429,0.8287123070847461
+0,65758,0.8433926267974765,0.8448841278248834,0.8162907587417658,0.8202673582113118,0.8159354518040114,0.8201126285674398,0.827943649586429,0.8287123070847461
+0,65758,0.8433926267974765,0.8448841278248834,0.8162907587417658,0.8202673582113118,0.8159354518040114,0.8201126285674398,0.827943649586429,0.8287123070847461
+0,65758,0.8433926267974765,0.8448841278248834,0.8162907587417658,0.8202673582113118,0.8159354518040114,0.8201126285674398,0.827943649586429,0.8287123070847461
+0,75152,0.8446040925038956,0.8448201918378135,0.8156779589594462,0.8197217831026785,0.8153511249507209,0.8195530071857927,0.8310105126796238,0.8314112536317299
+0,75152,0.8446040925038956,0.8448201918378135,0.8156779589594462,0.8197217831026785,0.8153511249507209,0.8195530071857927,0.8310105126796238,0.8314112536317299
+0,75152,0.8446040925038956,0.8448201918378135,0.8156779589594462,0.8197217831026785,0.8153511249507209,0.8195530071857927,0.8310105126796238,0.8314112536317299
+0,75152,0.8446040925038956,0.8448201918378135,0.8156779589594462,0.8197217831026785,0.8153511249507209,0.8195530071857927,0.8310105126796238,0.8314112536317299
+0,75152,0.8446040925038956,0.8448201918378135,0.8156779589594462,0.8197217831026785,0.8153511249507209,0.8195530071857927,0.8310105126796238,0.8314112536317299
+0,75152,0.8446040925038956,0.8448201918378135,0.8156779589594462,0.8197217831026785,0.8153511249507209,0.8195530071857927,0.8310105126796238,0.8314112536317299
+0,75152,0.8446040925038956,0.8448201918378135,0.8156779589594462,0.8197217831026785,0.8153511249507209,0.8195530071857927,0.8310105126796238,0.8314112536317299
+0,75152,0.8446040925038956,0.8448201918378135,0.8156779589594462,0.8197217831026785,0.8153511249507209,0.8195530071857927,0.8310105126796238,0.8314112536317299
+0,84546,0.843446814296738,0.8441162411753252,0.8163671546102611,0.8202042389507829,0.8161744627422614,0.8199274120869228,0.8304331386108932,0.8307216323112473
+0,84546,0.843446814296738,0.8441162411753252,0.8163671546102611,0.8202042389507829,0.8161744627422614,0.8199274120869228,0.8304331386108932,0.8307216323112473
+0,84546,0.843446814296738,0.8441162411753252,0.8163671546102611,0.8202042389507829,0.8161744627422614,0.8199274120869228,0.8304331386108932,0.8307216323112473
+0,84546,0.843446814296738,0.8441162411753252,0.8163671546102611,0.8202042389507829,0.8161744627422614,0.8199274120869228,0.8304331386108932,0.8307216323112473
+0,84546,0.843446814296738,0.8441162411753252,0.8163671546102611,0.8202042389507829,0.8161744627422614,0.8199274120869228,0.8304331386108932,0.8307216323112473
+0,84546,0.843446814296738,0.8441162411753252,0.8163671546102611,0.8202042389507829,0.8161744627422614,0.8199274120869228,0.8304331386108932,0.8307216323112473
+0,84546,0.843446814296738,0.8441162411753252,0.8163671546102611,0.8202042389507829,0.8161744627422614,0.8199274120869228,0.8304331386108932,0.8307216323112473
+0,84546,0.843446814296738,0.8441162411753252,0.8163671546102611,0.8202042389507829,0.8161744627422614,0.8199274120869228,0.8304331386108932,0.8307216323112473
+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
+0,93940,0.8437320757349038,0.8447999302580305,0.8158973728512129,0.8201478314386461,0.8156840205862232,0.8198638917414217,0.8310484448095099,0.8311148211939917
+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

modules.json

@@ -0,0 +1,14 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  }
+]

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9d3c6c29f5ecc7b55900689567b37c907ccadb4ab171b20bf9f88f0d16733611
+size 1340724401

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 75,
+  "do_lower_case": false
+}

similarity_evaluation_sts-test_results.csv

@@ -0,0 +1,9 @@
+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

special_tokens_map.json

@@ -0,0 +1 @@
+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

@@ -0,0 +1 @@
+{"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"}