peg_re

README.md

@@ -7,626 +7,14 @@ tags:
 - feature-extraction
 - sentence-similarity
 - transformers
-- mteb
-model-index:
-- name: PEG
-  results:
-  - task:
-      type: Reranking
-    dataset:
-      type: C-MTEB/CMedQAv1-reranking
-      name: MTEB CMedQAv1
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map
-      value: 84.09137463267582
-    - type: mrr
-      value: 86.6288888888889
-  - task:
-      type: Reranking
-    dataset:
-      type: C-MTEB/CMedQAv2-reranking
-      name: MTEB CMedQAv2
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map
-      value: 86.55765031914974
-    - type: mrr
-      value: 89.4325396825397
-  - task:
-      type: Retrieval
-    dataset:
-      type: C_MTEB/CmedqaRetrieval
-      name: MTEB CmedqaRetrieval
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 26.101000000000003
-    - type: map_at_10
-      value: 38.239000000000004
-    - type: map_at_100
-      value: 40.083
-    - type: map_at_1000
-      value: 40.205
-    - type: map_at_3
-      value: 34.386
-    - type: map_at_5
-      value: 36.425999999999995
-    - type: mrr_at_1
-      value: 39.434999999999995
-    - type: mrr_at_10
-      value: 46.967999999999996
-    - type: mrr_at_100
-      value: 47.946
-    - type: mrr_at_1000
-      value: 47.997
-    - type: mrr_at_3
-      value: 44.803
-    - type: mrr_at_5
-      value: 45.911
-    - type: ndcg_at_1
-      value: 39.434999999999995
-    - type: ndcg_at_10
-      value: 44.416
-    - type: ndcg_at_100
-      value: 51.773
-    - type: ndcg_at_1000
-      value: 53.888000000000005
-    - type: ndcg_at_3
-      value: 39.816
-    - type: ndcg_at_5
-      value: 41.467999999999996
-    - type: precision_at_1
-      value: 39.434999999999995
-    - type: precision_at_10
-      value: 9.786999999999999
-    - type: precision_at_100
-      value: 1.5810000000000002
-    - type: precision_at_1000
-      value: 0.184
-    - type: precision_at_3
-      value: 22.414
-    - type: precision_at_5
-      value: 15.943999999999999
-    - type: recall_at_1
-      value: 26.101000000000003
-    - type: recall_at_10
-      value: 53.82900000000001
-    - type: recall_at_100
-      value: 84.63199999999999
-    - type: recall_at_1000
-      value: 98.782
-    - type: recall_at_3
-      value: 39.585
-    - type: recall_at_5
-      value: 45.141
-  - task:
-      type: Retrieval
-    dataset:
-      type: C_MTEB/CovidRetrieval
-      name: MTEB CovidRetrieval
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 70.39
-    - type: map_at_10
-      value: 78.93599999999999
-    - type: map_at_100
-      value: 79.202
-    - type: map_at_1000
-      value: 79.205
-    - type: map_at_3
-      value: 77.538
-    - type: map_at_5
-      value: 78.312
-    - type: mrr_at_1
-      value: 70.706
-    - type: mrr_at_10
-      value: 79.018
-    - type: mrr_at_100
-      value: 79.28399999999999
-    - type: mrr_at_1000
-      value: 79.288
-    - type: mrr_at_3
-      value: 77.713
-    - type: mrr_at_5
-      value: 78.462
-    - type: ndcg_at_1
-      value: 70.601
-    - type: ndcg_at_10
-      value: 82.555
-    - type: ndcg_at_100
-      value: 83.718
-    - type: ndcg_at_1000
-      value: 83.855
-    - type: ndcg_at_3
-      value: 79.779
-    - type: ndcg_at_5
-      value: 81.149
-    - type: precision_at_1
-      value: 70.601
-    - type: precision_at_10
-      value: 9.463000000000001
-    - type: precision_at_100
-      value: 0.9979999999999999
-    - type: precision_at_1000
-      value: 0.101
-    - type: precision_at_3
-      value: 28.871999999999996
-    - type: precision_at_5
-      value: 18.019
-    - type: recall_at_1
-      value: 70.39
-    - type: recall_at_10
-      value: 93.572
-    - type: recall_at_100
-      value: 98.736
-    - type: recall_at_1000
-      value: 99.895
-    - type: recall_at_3
-      value: 86.091
-    - type: recall_at_5
-      value: 89.384
-  - task:
-      type: Retrieval
-    dataset:
-      type: C_MTEB/DuRetrieval
-      name: MTEB DuRetrieval
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 26.147
-    - type: map_at_10
-      value: 80.205
-    - type: map_at_100
-      value: 82.96
-    - type: map_at_1000
-      value: 82.999
-    - type: map_at_3
-      value: 55.16799999999999
-    - type: map_at_5
-      value: 69.798
-    - type: mrr_at_1
-      value: 89.8
-    - type: mrr_at_10
-      value: 93.16799999999999
-    - type: mrr_at_100
-      value: 93.22500000000001
-    - type: mrr_at_1000
-      value: 93.228
-    - type: mrr_at_3
-      value: 92.85
-    - type: mrr_at_5
-      value: 93.067
-    - type: ndcg_at_1
-      value: 89.8
-    - type: ndcg_at_10
-      value: 87.668
-    - type: ndcg_at_100
-      value: 90.16
-    - type: ndcg_at_1000
-      value: 90.505
-    - type: ndcg_at_3
-      value: 85.842
-    - type: ndcg_at_5
-      value: 85.101
-    - type: precision_at_1
-      value: 89.8
-    - type: precision_at_10
-      value: 42.225
-    - type: precision_at_100
-      value: 4.8149999999999995
-    - type: precision_at_1000
-      value: 0.48900000000000005
-    - type: precision_at_3
-      value: 76.967
-    - type: precision_at_5
-      value: 65.32
-    - type: recall_at_1
-      value: 26.147
-    - type: recall_at_10
-      value: 89.30399999999999
-    - type: recall_at_100
-      value: 97.609
-    - type: recall_at_1000
-      value: 99.409
-    - type: recall_at_3
-      value: 57.56
-    - type: recall_at_5
-      value: 74.78200000000001
-  - task:
-      type: Retrieval
-    dataset:
-      type: C_MTEB/EcomRetrieval
-      name: MTEB EcomRetrieval
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 53.300000000000004
-    - type: map_at_10
-      value: 62.507000000000005
-    - type: map_at_100
-      value: 63.068000000000005
-    - type: map_at_1000
-      value: 63.08200000000001
-    - type: map_at_3
-      value: 60.050000000000004
-    - type: map_at_5
-      value: 61.41
-    - type: mrr_at_1
-      value: 53.300000000000004
-    - type: mrr_at_10
-      value: 62.507000000000005
-    - type: mrr_at_100
-      value: 63.068000000000005
-    - type: mrr_at_1000
-      value: 63.08200000000001
-    - type: mrr_at_3
-      value: 60.050000000000004
-    - type: mrr_at_5
-      value: 61.41
-    - type: ndcg_at_1
-      value: 53.300000000000004
-    - type: ndcg_at_10
-      value: 67.31700000000001
-    - type: ndcg_at_100
-      value: 69.862
-    - type: ndcg_at_1000
-      value: 70.231
-    - type: ndcg_at_3
-      value: 62.222
-    - type: ndcg_at_5
-      value: 64.66300000000001
-    - type: precision_at_1
-      value: 53.300000000000004
-    - type: precision_at_10
-      value: 8.260000000000002
-    - type: precision_at_100
-      value: 0.941
-    - type: precision_at_1000
-      value: 0.097
-    - type: precision_at_3
-      value: 22.833000000000002
-    - type: precision_at_5
-      value: 14.879999999999999
-    - type: recall_at_1
-      value: 53.300000000000004
-    - type: recall_at_10
-      value: 82.6
-    - type: recall_at_100
-      value: 94.1
-    - type: recall_at_1000
-      value: 97.0
-    - type: recall_at_3
-      value: 68.5
-    - type: recall_at_5
-      value: 74.4
-  - task:
-      type: Retrieval
-    dataset:
-      type: C_MTEB/MMarcoRetrieval
-      name: MTEB MMarcoRetrieval
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 70.68799999999999
-    - type: map_at_10
-      value: 79.28399999999999
-    - type: map_at_100
-      value: 79.537
-    - type: map_at_1000
-      value: 79.545
-    - type: map_at_3
-      value: 77.643
-    - type: map_at_5
-      value: 78.694
-    - type: mrr_at_1
-      value: 73.05199999999999
-    - type: mrr_at_10
-      value: 79.794
-    - type: mrr_at_100
-      value: 80.024
-    - type: mrr_at_1000
-      value: 80.03099999999999
-    - type: mrr_at_3
-      value: 78.441
-    - type: mrr_at_5
-      value: 79.29
-    - type: ndcg_at_1
-      value: 73.05199999999999
-    - type: ndcg_at_10
-      value: 82.627
-    - type: ndcg_at_100
-      value: 83.737
-    - type: ndcg_at_1000
-      value: 83.946
-    - type: ndcg_at_3
-      value: 79.585
-    - type: ndcg_at_5
-      value: 81.306
-    - type: precision_at_1
-      value: 73.05199999999999
-    - type: precision_at_10
-      value: 9.835
-    - type: precision_at_100
-      value: 1.038
-    - type: precision_at_1000
-      value: 0.106
-    - type: precision_at_3
-      value: 29.756
-    - type: precision_at_5
-      value: 18.788
-    - type: recall_at_1
-      value: 70.68799999999999
-    - type: recall_at_10
-      value: 92.38300000000001
-    - type: recall_at_100
-      value: 97.347
-    - type: recall_at_1000
-      value: 98.992
-    - type: recall_at_3
-      value: 84.37
-    - type: recall_at_5
-      value: 88.434
-  - task:
-      type: Retrieval
-    dataset:
-      type: C_MTEB/MedicalRetrieval
-      name: MTEB MedicalRetrieval
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 53.1
-    - type: map_at_10
-      value: 58.36599999999999
-    - type: map_at_100
-      value: 58.939
-    - type: map_at_1000
-      value: 58.99100000000001
-    - type: map_at_3
-      value: 57.15
-    - type: map_at_5
-      value: 57.794999999999995
-    - type: mrr_at_1
-      value: 53.2
-    - type: mrr_at_10
-      value: 58.416000000000004
-    - type: mrr_at_100
-      value: 58.989999999999995
-    - type: mrr_at_1000
-      value: 59.041
-    - type: mrr_at_3
-      value: 57.199999999999996
-    - type: mrr_at_5
-      value: 57.845
-    - type: ndcg_at_1
-      value: 53.1
-    - type: ndcg_at_10
-      value: 60.989000000000004
-    - type: ndcg_at_100
-      value: 63.967
-    - type: ndcg_at_1000
-      value: 65.436
-    - type: ndcg_at_3
-      value: 58.425000000000004
-    - type: ndcg_at_5
-      value: 59.583
-    - type: precision_at_1
-      value: 53.1
-    - type: precision_at_10
-      value: 6.93
-    - type: precision_at_100
-      value: 0.8370000000000001
-    - type: precision_at_1000
-      value: 0.096
-    - type: precision_at_3
-      value: 20.7
-    - type: precision_at_5
-      value: 12.98
-    - type: recall_at_1
-      value: 53.1
-    - type: recall_at_10
-      value: 69.3
-    - type: recall_at_100
-      value: 83.7
-    - type: recall_at_1000
-      value: 95.5
-    - type: recall_at_3
-      value: 62.1
-    - type: recall_at_5
-      value: 64.9
-  - task:
-      type: Reranking
-    dataset:
-      type: C-MTEB/Mmarco-reranking
-      name: MTEB MMarcoReranking
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map
-      value: 33.548800108363665
-    - type: mrr
-      value: 32.529761904761905
-  - task:
-      type: Reranking
-    dataset:
-      type: C-MTEB/T2Reranking
-      name: MTEB T2Reranking
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map
-      value: 69.43381583724414
-    - type: mrr
-      value: 80.47879657392181
-  - task:
-      type: Retrieval
-    dataset:
-      type: C_MTEB/T2Retrieval
-      name: MTEB T2Retrieval
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 28.116000000000003
-    - type: map_at_10
-      value: 80.026
-    - type: map_at_100
-      value: 83.541
-    - type: map_at_1000
-      value: 83.592
-    - type: map_at_3
-      value: 56.092
-    - type: map_at_5
-      value: 69.114
-    - type: mrr_at_1
-      value: 91.557
-    - type: mrr_at_10
-      value: 93.73700000000001
-    - type: mrr_at_100
-      value: 93.808
-    - type: mrr_at_1000
-      value: 93.811
-    - type: mrr_at_3
-      value: 93.384
-    - type: mrr_at_5
-      value: 93.614
-    - type: ndcg_at_1
-      value: 91.553
-    - type: ndcg_at_10
-      value: 87.003
-    - type: ndcg_at_100
-      value: 90.128
-    - type: ndcg_at_1000
-      value: 90.615
-    - type: ndcg_at_3
-      value: 88.205
-    - type: ndcg_at_5
-      value: 86.978
-    - type: precision_at_1
-      value: 91.553
-    - type: precision_at_10
-      value: 43.25
-    - type: precision_at_100
-      value: 5.067
-    - type: precision_at_1000
-      value: 0.518
-    - type: precision_at_3
-      value: 77.25
-    - type: precision_at_5
-      value: 64.902
-    - type: recall_at_1
-      value: 28.116000000000003
-    - type: recall_at_10
-      value: 85.994
-    - type: recall_at_100
-      value: 96.345
-    - type: recall_at_1000
-      value: 98.867
-    - type: recall_at_3
-      value: 57.67099999999999
-    - type: recall_at_5
-      value: 72.26
-  - task:
-      type: Retrieval
-    dataset:
-      type: C_MTEB/VideoRetrieval
-      name: MTEB VideoRetrieval
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 64.9
-    - type: map_at_10
-      value: 73.763
-    - type: map_at_100
-      value: 74.116
-    - type: map_at_1000
-      value: 74.12100000000001
-    - type: map_at_3
-      value: 72.15
-    - type: map_at_5
-      value: 73.25
-    - type: mrr_at_1
-      value: 64.9
-    - type: mrr_at_10
-      value: 73.763
-    - type: mrr_at_100
-      value: 74.116
-    - type: mrr_at_1000
-      value: 74.12100000000001
-    - type: mrr_at_3
-      value: 72.15
-    - type: mrr_at_5
-      value: 73.25
-    - type: ndcg_at_1
-      value: 64.9
-    - type: ndcg_at_10
-      value: 77.639
-    - type: ndcg_at_100
-      value: 79.396
-    - type: ndcg_at_1000
-      value: 79.554
-    - type: ndcg_at_3
-      value: 74.406
-    - type: ndcg_at_5
-      value: 76.385
-    - type: precision_at_1
-      value: 64.9
-    - type: precision_at_10
-      value: 8.959999999999999
-    - type: precision_at_100
-      value: 0.979
-    - type: precision_at_1000
-      value: 0.099
-    - type: precision_at_3
-      value: 26.967000000000002
-    - type: precision_at_5
-      value: 17.14
-    - type: recall_at_1
-      value: 64.9
-    - type: recall_at_10
-      value: 89.60000000000001
-    - type: recall_at_100
-      value: 97.89999999999999
-    - type: recall_at_1000
-      value: 99.2
-    - type: recall_at_3
-      value: 80.9
-    - type: recall_at_5
-      value: 85.7
----
 license: apache-2.0
 library_name: transformers
 ---
 
-<h1 align="center">PEG: Towards Robust Text Retrieval with Progressive Learning</h1>
-
 ## Model Details
 We propose the PEG model (a Progressively Learned Textual Embedding), which progressively adjusts the weights of samples contributing to the loss within an extremely large batch, based on the difficulty levels of negative samples.
 we have amassed an extensive collection of over 110 million data, spanning a wide range of fields such as general knowledge, finance, tourism, medicine, and more.
 
-Our technical report is available at [Paper](https://arxiv.org/pdf/2311.11691.pdf)
 
 ## Usage (HuggingFace Transformers)
 
@@ -654,24 +42,4 @@ with torch.no_grad():
     embeddings = last_hidden_state[:, 0]
 print("embeddings:")
 print(embeddings)
-```
-
-## Contact
-If you have any question or suggestion related to this project, feel free to open an issue or pull request.
-You also can email Tong Wu(townswu@tencent.com). 
-
-
-## Citation
-
-If you find our work helpful for your research, please consider citing the following BibTeX entry:
-
-```
-
-@article{wu2023towards,
-  title={Towards Robust Text Retrieval with Progressive Learning},
-  author={Wu, Tong and Qin, Yulei and Zhang, Enwei and Xu, Zihan and Gao, Yuting and Li, Ke and Sun, Xing},
-  journal={arXiv preprint arXiv:2311.11691},
-  year={2023}
-}
-
 ```

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "PEG",
+  "_name_or_path": "/mnt/data/townswu/ckpts/BAAI-bge-large-zh",
   "architectures": [
     "BertModel"
   ],

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0c4b6632f3d3e73934d73476b17afe1f648c043f07add3536e332ec359ec723e
-size 651175661
+oid sha256:04b94b1bf0b3e8d8c5f0560f7778975afffff6ee2fc96628be1a4bb999ad2845
+size 1302218477