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GritLM_-_GritLM-7B-4bits
RichardErkhov/GritLM_-_GritLM-7B-4bits
GritLM_-_GritLM-7B-4bits is a text generation model from RichardErkhov. Use it when you need the model to write or continue text. It is set up for transformers.
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Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
GritLM-7B - bnb 4bits
- Model creator: https://huggingface.co/GritLM/
- Original model: https://huggingface.co/GritLM/GritLM-7B/
Original model description:
pipeline_tag: text-generation inference: true license: apache-2.0 datasets:
- GritLM/tulu2 tags:
- mteb model-index:
- name: GritLM-7B
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy value: 81.17910447761194
- type: ap value: 46.26260671758199
- type: f1 value: 75.44565719934167
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy value: 96.5161
- type: ap value: 94.79131981460425
- type: f1 value: 96.51506148413065
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy value: 57.806000000000004
- type: f1 value: 56.78350156257903
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 38.478
- type: map_at_10 value: 54.955
- type: map_at_100 value: 54.955
- type: map_at_1000 value: 54.955
- type: map_at_3 value: 50.888999999999996
- type: map_at_5 value: 53.349999999999994
- type: mrr_at_1 value: 39.757999999999996
- type: mrr_at_10 value: 55.449000000000005
- type: mrr_at_100 value: 55.449000000000005
- type: mrr_at_1000 value: 55.449000000000005
- type: mrr_at_3 value: 51.37500000000001
- type: mrr_at_5 value: 53.822
- type: ndcg_at_1 value: 38.478
- type: ndcg_at_10 value: 63.239999999999995
- type: ndcg_at_100 value: 63.239999999999995
- type: ndcg_at_1000 value: 63.239999999999995
- type: ndcg_at_3 value: 54.935
- type: ndcg_at_5 value: 59.379000000000005
- type: precision_at_1 value: 38.478
- type: precision_at_10 value: 8.933
- type: precision_at_100 value: 0.893
- type: precision_at_1000 value: 0.089
- type: precision_at_3 value: 22.214
- type: precision_at_5 value: 15.491
- type: recall_at_1 value: 38.478
- type: recall_at_10 value: 89.331
- type: recall_at_100 value: 89.331
- type: recall_at_1000 value: 89.331
- type: recall_at_3 value: 66.643
- type: recall_at_5 value: 77.45400000000001
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure value: 51.67144081472449
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure value: 48.11256154264126
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map value: 67.33801955487878
- type: mrr value: 80.71549487754474
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson value: 88.1935203751726
- type: cos_sim_spearman value: 86.35497970498659
- type: euclidean_pearson value: 85.46910708503744
- type: euclidean_spearman value: 85.13928935405485
- type: manhattan_pearson value: 85.68373836333303
- type: manhattan_spearman value: 85.40013867117746
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy value: 88.46753246753248
- type: f1 value: 88.43006344981134
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure value: 40.86793640310432
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure value: 39.80291334130727
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 38.421
- type: map_at_10 value: 52.349000000000004
- type: map_at_100 value: 52.349000000000004
- type: map_at_1000 value: 52.349000000000004
- type: map_at_3 value: 48.17
- type: map_at_5 value: 50.432
- type: mrr_at_1 value: 47.353
- type: mrr_at_10 value: 58.387
- type: mrr_at_100 value: 58.387
- type: mrr_at_1000 value: 58.387
- type: mrr_at_3 value: 56.199
- type: mrr_at_5 value: 57.487
- type: ndcg_at_1 value: 47.353
- type: ndcg_at_10 value: 59.202
- type: ndcg_at_100 value: 58.848
- type: ndcg_at_1000 value: 58.831999999999994
- type: ndcg_at_3 value: 54.112
- type: ndcg_at_5 value: 56.312
- type: precision_at_1 value: 47.353
- type: precision_at_10 value: 11.459
- type: precision_at_100 value: 1.146
- type: precision_at_1000 value: 0.11499999999999999
- type: precision_at_3 value: 26.133
- type: precision_at_5 value: 18.627
- type: recall_at_1 value: 38.421
- type: recall_at_10 value: 71.89
- type: recall_at_100 value: 71.89
- type: recall_at_1000 value: 71.89
- type: recall_at_3 value: 56.58
- type: recall_at_5 value: 63.125
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 38.025999999999996
- type: map_at_10 value: 50.590999999999994
- type: map_at_100 value: 51.99700000000001
- type: map_at_1000 value: 52.11599999999999
- type: map_at_3 value: 47.435
- type: map_at_5 value: 49.236000000000004
- type: mrr_at_1 value: 48.28
- type: mrr_at_10 value: 56.814
- type: mrr_at_100 value: 57.446
- type: mrr_at_1000 value: 57.476000000000006
- type: mrr_at_3 value: 54.958
- type: mrr_at_5 value: 56.084999999999994
- type: ndcg_at_1 value: 48.28
- type: ndcg_at_10 value: 56.442
- type: ndcg_at_100 value: 60.651999999999994
- type: ndcg_at_1000 value: 62.187000000000005
- type: ndcg_at_3 value: 52.866
- type: ndcg_at_5 value: 54.515
- type: precision_at_1 value: 48.28
- type: precision_at_10 value: 10.586
- type: precision_at_100 value: 1.6310000000000002
- type: precision_at_1000 value: 0.20600000000000002
- type: precision_at_3 value: 25.945
- type: precision_at_5 value: 18.076
- type: recall_at_1 value: 38.025999999999996
- type: recall_at_10 value: 66.11399999999999
- type: recall_at_100 value: 83.339
- type: recall_at_1000 value: 92.413
- type: recall_at_3 value: 54.493
- type: recall_at_5 value: 59.64699999999999
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 47.905
- type: map_at_10 value: 61.58
- type: map_at_100 value: 62.605
- type: map_at_1000 value: 62.637
- type: map_at_3 value: 58.074000000000005
- type: map_at_5 value: 60.260000000000005
- type: mrr_at_1 value: 54.42
- type: mrr_at_10 value: 64.847
- type: mrr_at_100 value: 65.403
- type: mrr_at_1000 value: 65.41900000000001
- type: mrr_at_3 value: 62.675000000000004
- type: mrr_at_5 value: 64.101
- type: ndcg_at_1 value: 54.42
- type: ndcg_at_10 value: 67.394
- type: ndcg_at_100 value: 70.846
- type: ndcg_at_1000 value: 71.403
- type: ndcg_at_3 value: 62.025
- type: ndcg_at_5 value: 65.032
- type: precision_at_1 value: 54.42
- type: precision_at_10 value: 10.646
- type: precision_at_100 value: 1.325
- type: precision_at_1000 value: 0.13999999999999999
- type: precision_at_3 value: 27.398
- type: precision_at_5 value: 18.796
- type: recall_at_1 value: 47.905
- type: recall_at_10 value: 80.84599999999999
- type: recall_at_100 value: 95.078
- type: recall_at_1000 value: 98.878
- type: recall_at_3 value: 67.05600000000001
- type: recall_at_5 value: 74.261
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 30.745
- type: map_at_10 value: 41.021
- type: map_at_100 value: 41.021
- type: map_at_1000 value: 41.021
- type: map_at_3 value: 37.714999999999996
- type: map_at_5 value: 39.766
- type: mrr_at_1 value: 33.559
- type: mrr_at_10 value: 43.537
- type: mrr_at_100 value: 43.537
- type: mrr_at_1000 value: 43.537
- type: mrr_at_3 value: 40.546
- type: mrr_at_5 value: 42.439
- type: ndcg_at_1 value: 33.559
- type: ndcg_at_10 value: 46.781
- type: ndcg_at_100 value: 46.781
- type: ndcg_at_1000 value: 46.781
- type: ndcg_at_3 value: 40.516000000000005
- type: ndcg_at_5 value: 43.957
- type: precision_at_1 value: 33.559
- type: precision_at_10 value: 7.198
- type: precision_at_100 value: 0.72
- type: precision_at_1000 value: 0.07200000000000001
- type: precision_at_3 value: 17.1
- type: precision_at_5 value: 12.316
- type: recall_at_1 value: 30.745
- type: recall_at_10 value: 62.038000000000004
- type: recall_at_100 value: 62.038000000000004
- type: recall_at_1000 value: 62.038000000000004
- type: recall_at_3 value: 45.378
- type: recall_at_5 value: 53.580000000000005
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 19.637999999999998
- type: map_at_10 value: 31.05
- type: map_at_100 value: 31.05
- type: map_at_1000 value: 31.05
- type: map_at_3 value: 27.628000000000004
- type: map_at_5 value: 29.767
- type: mrr_at_1 value: 25.0
- type: mrr_at_10 value: 36.131
- type: mrr_at_100 value: 36.131
- type: mrr_at_1000 value: 36.131
- type: mrr_at_3 value: 33.333
- type: mrr_at_5 value: 35.143
- type: ndcg_at_1 value: 25.0
- type: ndcg_at_10 value: 37.478
- type: ndcg_at_100 value: 37.469
- type: ndcg_at_1000 value: 37.469
- type: ndcg_at_3 value: 31.757999999999996
- type: ndcg_at_5 value: 34.821999999999996
- type: precision_at_1 value: 25.0
- type: precision_at_10 value: 7.188999999999999
- type: precision_at_100 value: 0.719
- type: precision_at_1000 value: 0.07200000000000001
- type: precision_at_3 value: 15.837000000000002
- type: precision_at_5 value: 11.841
- type: recall_at_1 value: 19.637999999999998
- type: recall_at_10 value: 51.836000000000006
- type: recall_at_100 value: 51.836000000000006
- type: recall_at_1000 value: 51.836000000000006
- type: recall_at_3 value: 36.384
- type: recall_at_5 value: 43.964
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 34.884
- type: map_at_10 value: 47.88
- type: map_at_100 value: 47.88
- type: map_at_1000 value: 47.88
- type: map_at_3 value: 43.85
- type: map_at_5 value: 46.414
- type: mrr_at_1 value: 43.022
- type: mrr_at_10 value: 53.569
- type: mrr_at_100 value: 53.569
- type: mrr_at_1000 value: 53.569
- type: mrr_at_3 value: 51.075
- type: mrr_at_5 value: 52.725
- type: ndcg_at_1 value: 43.022
- type: ndcg_at_10 value: 54.461000000000006
- type: ndcg_at_100 value: 54.388000000000005
- type: ndcg_at_1000 value: 54.388000000000005
- type: ndcg_at_3 value: 48.864999999999995
- type: ndcg_at_5 value: 52.032000000000004
- type: precision_at_1 value: 43.022
- type: precision_at_10 value: 9.885
- type: precision_at_100 value: 0.988
- type: precision_at_1000 value: 0.099
- type: precision_at_3 value: 23.612
- type: precision_at_5 value: 16.997
- type: recall_at_1 value: 34.884
- type: recall_at_10 value: 68.12899999999999
- type: recall_at_100 value: 68.12899999999999
- type: recall_at_1000 value: 68.12899999999999
- type: recall_at_3 value: 52.428
- type: recall_at_5 value: 60.662000000000006
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 31.588
- type: map_at_10 value: 43.85
- type: map_at_100 value: 45.317
- type: map_at_1000 value: 45.408
- type: map_at_3 value: 39.73
- type: map_at_5 value: 42.122
- type: mrr_at_1 value: 38.927
- type: mrr_at_10 value: 49.582
- type: mrr_at_100 value: 50.39
- type: mrr_at_1000 value: 50.426
- type: mrr_at_3 value: 46.518
- type: mrr_at_5 value: 48.271
- type: ndcg_at_1 value: 38.927
- type: ndcg_at_10 value: 50.605999999999995
- type: ndcg_at_100 value: 56.22200000000001
- type: ndcg_at_1000 value: 57.724
- type: ndcg_at_3 value: 44.232
- type: ndcg_at_5 value: 47.233999999999995
- type: precision_at_1 value: 38.927
- type: precision_at_10 value: 9.429
- type: precision_at_100 value: 1.435
- type: precision_at_1000 value: 0.172
- type: precision_at_3 value: 21.271
- type: precision_at_5 value: 15.434000000000001
- type: recall_at_1 value: 31.588
- type: recall_at_10 value: 64.836
- type: recall_at_100 value: 88.066
- type: recall_at_1000 value: 97.748
- type: recall_at_3 value: 47.128
- type: recall_at_5 value: 54.954
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 31.956083333333336
- type: map_at_10 value: 43.33483333333333
- type: map_at_100 value: 44.64883333333333
- type: map_at_1000 value: 44.75
- type: map_at_3 value: 39.87741666666666
- type: map_at_5 value: 41.86766666666667
- type: mrr_at_1 value: 38.06341666666667
- type: mrr_at_10 value: 47.839666666666666
- type: mrr_at_100 value: 48.644000000000005
- type: mrr_at_1000 value: 48.68566666666667
- type: mrr_at_3 value: 45.26358333333334
- type: mrr_at_5 value: 46.790000000000006
- type: ndcg_at_1 value: 38.06341666666667
- type: ndcg_at_10 value: 49.419333333333334
- type: ndcg_at_100 value: 54.50166666666667
- type: ndcg_at_1000 value: 56.161166666666674
- type: ndcg_at_3 value: 43.982416666666666
- type: ndcg_at_5 value: 46.638083333333334
- type: precision_at_1 value: 38.06341666666667
- type: precision_at_10 value: 8.70858333333333
- type: precision_at_100 value: 1.327
- type: precision_at_1000 value: 0.165
- type: precision_at_3 value: 20.37816666666667
- type: precision_at_5 value: 14.516333333333334
- type: recall_at_1 value: 31.956083333333336
- type: recall_at_10 value: 62.69458333333334
- type: recall_at_100 value: 84.46433333333334
- type: recall_at_1000 value: 95.58449999999999
- type: recall_at_3 value: 47.52016666666666
- type: recall_at_5 value: 54.36066666666666
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 28.912
- type: map_at_10 value: 38.291
- type: map_at_100 value: 39.44
- type: map_at_1000 value: 39.528
- type: map_at_3 value: 35.638
- type: map_at_5 value: 37.218
- type: mrr_at_1 value: 32.822
- type: mrr_at_10 value: 41.661
- type: mrr_at_100 value: 42.546
- type: mrr_at_1000 value: 42.603
- type: mrr_at_3 value: 39.238
- type: mrr_at_5 value: 40.726
- type: ndcg_at_1 value: 32.822
- type: ndcg_at_10 value: 43.373
- type: ndcg_at_100 value: 48.638
- type: ndcg_at_1000 value: 50.654999999999994
- type: ndcg_at_3 value: 38.643
- type: ndcg_at_5 value: 41.126000000000005
- type: precision_at_1 value: 32.822
- type: precision_at_10 value: 6.8709999999999996
- type: precision_at_100 value: 1.032
- type: precision_at_1000 value: 0.128
- type: precision_at_3 value: 16.82
- type: precision_at_5 value: 11.718
- type: recall_at_1 value: 28.912
- type: recall_at_10 value: 55.376999999999995
- type: recall_at_100 value: 79.066
- type: recall_at_1000 value: 93.664
- type: recall_at_3 value: 42.569
- type: recall_at_5 value: 48.719
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 22.181
- type: map_at_10 value: 31.462
- type: map_at_100 value: 32.73
- type: map_at_1000 value: 32.848
- type: map_at_3 value: 28.57
- type: map_at_5 value: 30.182
- type: mrr_at_1 value: 27.185
- type: mrr_at_10 value: 35.846000000000004
- type: mrr_at_100 value: 36.811
- type: mrr_at_1000 value: 36.873
- type: mrr_at_3 value: 33.437
- type: mrr_at_5 value: 34.813
- type: ndcg_at_1 value: 27.185
- type: ndcg_at_10 value: 36.858000000000004
- type: ndcg_at_100 value: 42.501
- type: ndcg_at_1000 value: 44.945
- type: ndcg_at_3 value: 32.066
- type: ndcg_at_5 value: 34.29
- type: precision_at_1 value: 27.185
- type: precision_at_10 value: 6.752
- type: precision_at_100 value: 1.111
- type: precision_at_1000 value: 0.151
- type: precision_at_3 value: 15.290000000000001
- type: precision_at_5 value: 11.004999999999999
- type: recall_at_1 value: 22.181
- type: recall_at_10 value: 48.513
- type: recall_at_100 value: 73.418
- type: recall_at_1000 value: 90.306
- type: recall_at_3 value: 35.003
- type: recall_at_5 value: 40.876000000000005
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 33.934999999999995
- type: map_at_10 value: 44.727
- type: map_at_100 value: 44.727
- type: map_at_1000 value: 44.727
- type: map_at_3 value: 40.918
- type: map_at_5 value: 42.961
- type: mrr_at_1 value: 39.646
- type: mrr_at_10 value: 48.898
- type: mrr_at_100 value: 48.898
- type: mrr_at_1000 value: 48.898
- type: mrr_at_3 value: 45.896
- type: mrr_at_5 value: 47.514
- type: ndcg_at_1 value: 39.646
- type: ndcg_at_10 value: 50.817
- type: ndcg_at_100 value: 50.803
- type: ndcg_at_1000 value: 50.803
- type: ndcg_at_3 value: 44.507999999999996
- type: ndcg_at_5 value: 47.259
- type: precision_at_1 value: 39.646
- type: precision_at_10 value: 8.759
- type: precision_at_100 value: 0.876
- type: precision_at_1000 value: 0.08800000000000001
- type: precision_at_3 value: 20.274
- type: precision_at_5 value: 14.366000000000001
- type: recall_at_1 value: 33.934999999999995
- type: recall_at_10 value: 65.037
- type: recall_at_100 value: 65.037
- type: recall_at_1000 value: 65.037
- type: recall_at_3 value: 47.439
- type: recall_at_5 value: 54.567
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 32.058
- type: map_at_10 value: 43.137
- type: map_at_100 value: 43.137
- type: map_at_1000 value: 43.137
- type: map_at_3 value: 39.882
- type: map_at_5 value: 41.379
- type: mrr_at_1 value: 38.933
- type: mrr_at_10 value: 48.344
- type: mrr_at_100 value: 48.344
- type: mrr_at_1000 value: 48.344
- type: mrr_at_3 value: 45.652
- type: mrr_at_5 value: 46.877
- type: ndcg_at_1 value: 38.933
- type: ndcg_at_10 value: 49.964
- type: ndcg_at_100 value: 49.242000000000004
- type: ndcg_at_1000 value: 49.222
- type: ndcg_at_3 value: 44.605
- type: ndcg_at_5 value: 46.501999999999995
- type: precision_at_1 value: 38.933
- type: precision_at_10 value: 9.427000000000001
- type: precision_at_100 value: 0.943
- type: precision_at_1000 value: 0.094
- type: precision_at_3 value: 20.685000000000002
- type: precision_at_5 value: 14.585
- type: recall_at_1 value: 32.058
- type: recall_at_10 value: 63.074
- type: recall_at_100 value: 63.074
- type: recall_at_1000 value: 63.074
- type: recall_at_3 value: 47.509
- type: recall_at_5 value: 52.455
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 26.029000000000003
- type: map_at_10 value: 34.646
- type: map_at_100 value: 34.646
- type: map_at_1000 value: 34.646
- type: map_at_3 value: 31.456
- type: map_at_5 value: 33.138
- type: mrr_at_1 value: 28.281
- type: mrr_at_10 value: 36.905
- type: mrr_at_100 value: 36.905
- type: mrr_at_1000 value: 36.905
- type: mrr_at_3 value: 34.011
- type: mrr_at_5 value: 35.638
- type: ndcg_at_1 value: 28.281
- type: ndcg_at_10 value: 40.159
- type: ndcg_at_100 value: 40.159
- type: ndcg_at_1000 value: 40.159
- type: ndcg_at_3 value: 33.995
- type: ndcg_at_5 value: 36.836999999999996
- type: precision_at_1 value: 28.281
- type: precision_at_10 value: 6.358999999999999
- type: precision_at_100 value: 0.636
- type: precision_at_1000 value: 0.064
- type: precision_at_3 value: 14.233
- type: precision_at_5 value: 10.314
- type: recall_at_1 value: 26.029000000000003
- type: recall_at_10 value: 55.08
- type: recall_at_100 value: 55.08
- type: recall_at_1000 value: 55.08
- type: recall_at_3 value: 38.487
- type: recall_at_5 value: 45.308
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 12.842999999999998
- type: map_at_10 value: 22.101000000000003
- type: map_at_100 value: 24.319
- type: map_at_1000 value: 24.51
- type: map_at_3 value: 18.372
- type: map_at_5 value: 20.323
- type: mrr_at_1 value: 27.948
- type: mrr_at_10 value: 40.321
- type: mrr_at_100 value: 41.262
- type: mrr_at_1000 value: 41.297
- type: mrr_at_3 value: 36.558
- type: mrr_at_5 value: 38.824999999999996
- type: ndcg_at_1 value: 27.948
- type: ndcg_at_10 value: 30.906
- type: ndcg_at_100 value: 38.986
- type: ndcg_at_1000 value: 42.136
- type: ndcg_at_3 value: 24.911
- type: ndcg_at_5 value: 27.168999999999997
- type: precision_at_1 value: 27.948
- type: precision_at_10 value: 9.798
- type: precision_at_100 value: 1.8399999999999999
- type: precision_at_1000 value: 0.243
- type: precision_at_3 value: 18.328
- type: precision_at_5 value: 14.502
- type: recall_at_1 value: 12.842999999999998
- type: recall_at_10 value: 37.245
- type: recall_at_100 value: 64.769
- type: recall_at_1000 value: 82.055
- type: recall_at_3 value: 23.159
- type: recall_at_5 value: 29.113
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 8.934000000000001
- type: map_at_10 value: 21.915000000000003
- type: map_at_100 value: 21.915000000000003
- type: map_at_1000 value: 21.915000000000003
- type: map_at_3 value: 14.623
- type: map_at_5 value: 17.841
- type: mrr_at_1 value: 71.25
- type: mrr_at_10 value: 78.994
- type: mrr_at_100 value: 78.994
- type: mrr_at_1000 value: 78.994
- type: mrr_at_3 value: 77.208
- type: mrr_at_5 value: 78.55799999999999
- type: ndcg_at_1 value: 60.62499999999999
- type: ndcg_at_10 value: 46.604
- type: ndcg_at_100 value: 35.653
- type: ndcg_at_1000 value: 35.531
- type: ndcg_at_3 value: 50.605
- type: ndcg_at_5 value: 48.730000000000004
- type: precision_at_1 value: 71.25
- type: precision_at_10 value: 37.75
- type: precision_at_100 value: 3.775
- type: precision_at_1000 value: 0.377
- type: precision_at_3 value: 54.417
- type: precision_at_5 value: 48.15
- type: recall_at_1 value: 8.934000000000001
- type: recall_at_10 value: 28.471000000000004
- type: recall_at_100 value: 28.471000000000004
- type: recall_at_1000 value: 28.471000000000004
- type: recall_at_3 value: 16.019
- type: recall_at_5 value: 21.410999999999998
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy value: 52.81
- type: f1 value: 47.987573380720114
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 66.81899999999999
- type: map_at_10 value: 78.034
- type: map_at_100 value: 78.034
- type: map_at_1000 value: 78.034
- type: map_at_3 value: 76.43100000000001
- type: map_at_5 value: 77.515
- type: mrr_at_1 value: 71.542
- type: mrr_at_10 value: 81.638
- type: mrr_at_100 value: 81.638
- type: mrr_at_1000 value: 81.638
- type: mrr_at_3 value: 80.403
- type: mrr_at_5 value: 81.256
- type: ndcg_at_1 value: 71.542
- type: ndcg_at_10 value: 82.742
- type: ndcg_at_100 value: 82.741
- type: ndcg_at_1000 value: 82.741
- type: ndcg_at_3 value: 80.039
- type: ndcg_at_5 value: 81.695
- type: precision_at_1 value: 71.542
- type: precision_at_10 value: 10.387
- type: precision_at_100 value: 1.039
- type: precision_at_1000 value: 0.104
- type: precision_at_3 value: 31.447999999999997
- type: precision_at_5 value: 19.91
- type: recall_at_1 value: 66.81899999999999
- type: recall_at_10 value: 93.372
- type: recall_at_100 value: 93.372
- type: recall_at_1000 value: 93.372
- type: recall_at_3 value: 86.33
- type: recall_at_5 value: 90.347
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 31.158
- type: map_at_10 value: 52.017
- type: map_at_100 value: 54.259
- type: map_at_1000 value: 54.367
- type: map_at_3 value: 45.738
- type: map_at_5 value: 49.283
- type: mrr_at_1 value: 57.87
- type: mrr_at_10 value: 66.215
- type: mrr_at_100 value: 66.735
- type: mrr_at_1000 value: 66.75
- type: mrr_at_3 value: 64.043
- type: mrr_at_5 value: 65.116
- type: ndcg_at_1 value: 57.87
- type: ndcg_at_10 value: 59.946999999999996
- type: ndcg_at_100 value: 66.31099999999999
- type: ndcg_at_1000 value: 67.75999999999999
- type: ndcg_at_3 value: 55.483000000000004
- type: ndcg_at_5 value: 56.891000000000005
- type: precision_at_1 value: 57.87
- type: precision_at_10 value: 16.497
- type: precision_at_100 value: 2.321
- type: precision_at_1000 value: 0.258
- type: precision_at_3 value: 37.14
- type: precision_at_5 value: 27.067999999999998
- type: recall_at_1 value: 31.158
- type: recall_at_10 value: 67.381
- type: recall_at_100 value: 89.464
- type: recall_at_1000 value: 97.989
- type: recall_at_3 value: 50.553000000000004
- type: recall_at_5 value: 57.824
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 42.073
- type: map_at_10 value: 72.418
- type: map_at_100 value: 73.175
- type: map_at_1000 value: 73.215
- type: map_at_3 value: 68.791
- type: map_at_5 value: 71.19
- type: mrr_at_1 value: 84.146
- type: mrr_at_10 value: 88.994
- type: mrr_at_100 value: 89.116
- type: mrr_at_1000 value: 89.12
- type: mrr_at_3 value: 88.373
- type: mrr_at_5 value: 88.82
- type: ndcg_at_1 value: 84.146
- type: ndcg_at_10 value: 79.404
- type: ndcg_at_100 value: 81.83200000000001
- type: ndcg_at_1000 value: 82.524
- type: ndcg_at_3 value: 74.595
- type: ndcg_at_5 value: 77.474
- type: precision_at_1 value: 84.146
- type: precision_at_10 value: 16.753999999999998
- type: precision_at_100 value: 1.8599999999999999
- type: precision_at_1000 value: 0.19499999999999998
- type: precision_at_3 value: 48.854
- type: precision_at_5 value: 31.579
- type: recall_at_1 value: 42.073
- type: recall_at_10 value: 83.768
- type: recall_at_100 value: 93.018
- type: recall_at_1000 value: 97.481
- type: recall_at_3 value: 73.282
- type: recall_at_5 value: 78.947
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy value: 94.9968
- type: ap value: 92.93892195862824
- type: f1 value: 94.99327998213761
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1 value: 21.698
- type: map_at_10 value: 34.585
- type: map_at_100 value: 35.782000000000004
- type: map_at_1000 value: 35.825
- type: map_at_3 value: 30.397999999999996
- type: map_at_5 value: 32.72
- type: mrr_at_1 value: 22.192
- type: mrr_at_10 value: 35.085
- type: mrr_at_100 value: 36.218
- type: mrr_at_1000 value: 36.256
- type: mrr_at_3 value: 30.986000000000004
- type: mrr_at_5 value: 33.268
- type: ndcg_at_1 value: 22.192
- type: ndcg_at_10 value: 41.957
- type: ndcg_at_100 value: 47.658
- type: ndcg_at_1000 value: 48.697
- type: ndcg_at_3 value: 33.433
- type: ndcg_at_5 value: 37.551
- type: precision_at_1 value: 22.192
- type: precision_at_10 value: 6.781
- type: precision_at_100 value: 0.963
- type: precision_at_1000 value: 0.105
- type: precision_at_3 value: 14.365
- type: precision_at_5 value: 10.713000000000001
- type: recall_at_1 value: 21.698
- type: recall_at_10 value: 64.79
- type: recall_at_100 value: 91.071
- type: recall_at_1000 value: 98.883
- type: recall_at_3 value: 41.611
- type: recall_at_5 value: 51.459999999999994
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy value: 96.15823073415413
- type: f1 value: 96.00362034963248
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy value: 87.12722298221614
- type: f1 value: 70.46888967516227
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 80.77673167451245
- type: f1 value: 77.60202561132175
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 82.09145931405514
- type: f1 value: 81.7701921473406
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure value: 36.52153488185864
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure value: 36.80090398444147
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map value: 31.807141746058605
- type: mrr value: 32.85025611455029
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 6.920999999999999
- type: map_at_10 value: 16.049
- type: map_at_100 value: 16.049
- type: map_at_1000 value: 16.049
- type: map_at_3 value: 11.865
- type: map_at_5 value: 13.657
- type: mrr_at_1 value: 53.87
- type: mrr_at_10 value: 62.291
- type: mrr_at_100 value: 62.291
- type: mrr_at_1000 value: 62.291
- type: mrr_at_3 value: 60.681
- type: mrr_at_5 value: 61.61
- type: ndcg_at_1 value: 51.23799999999999
- type: ndcg_at_10 value: 40.892
- type: ndcg_at_100 value: 26.951999999999998
- type: ndcg_at_1000 value: 26.474999999999998
- type: ndcg_at_3 value: 46.821
- type: ndcg_at_5 value: 44.333
- type: precision_at_1 value: 53.251000000000005
- type: precision_at_10 value: 30.124000000000002
- type: precision_at_100 value: 3.012
- type: precision_at_1000 value: 0.301
- type: precision_at_3 value: 43.55
- type: precision_at_5 value: 38.266
- type: recall_at_1 value: 6.920999999999999
- type: recall_at_10 value: 20.852
- type: recall_at_100 value: 20.852
- type: recall_at_1000 value: 20.852
- type: recall_at_3 value: 13.628000000000002
- type: recall_at_5 value: 16.273
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 46.827999999999996
- type: map_at_10 value: 63.434000000000005
- type: map_at_100 value: 63.434000000000005
- type: map_at_1000 value: 63.434000000000005
- type: map_at_3 value: 59.794000000000004
- type: map_at_5 value: 62.08
- type: mrr_at_1 value: 52.288999999999994
- type: mrr_at_10 value: 65.95
- type: mrr_at_100 value: 65.95
- type: mrr_at_1000 value: 65.95
- type: mrr_at_3 value: 63.413
- type: mrr_at_5 value: 65.08
- type: ndcg_at_1 value: 52.288999999999994
- type: ndcg_at_10 value: 70.301
- type: ndcg_at_100 value: 70.301
- type: ndcg_at_1000 value: 70.301
- type: ndcg_at_3 value: 63.979
- type: ndcg_at_5 value: 67.582
- type: precision_at_1 value: 52.288999999999994
- type: precision_at_10 value: 10.576
- type: precision_at_100 value: 1.058
- type: precision_at_1000 value: 0.106
- type: precision_at_3 value: 28.177000000000003
- type: precision_at_5 value: 19.073
- type: recall_at_1 value: 46.827999999999996
- type: recall_at_10 value: 88.236
- type: recall_at_100 value: 88.236
- type: recall_at_1000 value: 88.236
- type: recall_at_3 value: 72.371
- type: recall_at_5 value: 80.56
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 71.652
- type: map_at_10 value: 85.953
- type: map_at_100 value: 85.953
- type: map_at_1000 value: 85.953
- type: map_at_3 value: 83.05399999999999
- type: map_at_5 value: 84.89
- type: mrr_at_1 value: 82.42
- type: mrr_at_10 value: 88.473
- type: mrr_at_100 value: 88.473
- type: mrr_at_1000 value: 88.473
- type: mrr_at_3 value: 87.592
- type: mrr_at_5 value: 88.211
- type: ndcg_at_1 value: 82.44
- type: ndcg_at_10 value: 89.467
- type: ndcg_at_100 value: 89.33
- type: ndcg_at_1000 value: 89.33
- type: ndcg_at_3 value: 86.822
- type: ndcg_at_5 value: 88.307
- type: precision_at_1 value: 82.44
- type: precision_at_10 value: 13.616
- type: precision_at_100 value: 1.362
- type: precision_at_1000 value: 0.136
- type: precision_at_3 value: 38.117000000000004
- type: precision_at_5 value: 25.05
- type: recall_at_1 value: 71.652
- type: recall_at_10 value: 96.224
- type: recall_at_100 value: 96.224
- type: recall_at_1000 value: 96.224
- type: recall_at_3 value: 88.571
- type: recall_at_5 value: 92.812
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure value: 61.295010338050474
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure value: 67.26380819328142
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 5.683
- type: map_at_10 value: 14.924999999999999
- type: map_at_100 value: 17.532
- type: map_at_1000 value: 17.875
- type: map_at_3 value: 10.392
- type: map_at_5 value: 12.592
- type: mrr_at_1 value: 28.000000000000004
- type: mrr_at_10 value: 39.951
- type: mrr_at_100 value: 41.025
- type: mrr_at_1000 value: 41.056
- type: mrr_at_3 value: 36.317
- type: mrr_at_5 value: 38.412
- type: ndcg_at_1 value: 28.000000000000004
- type: ndcg_at_10 value: 24.410999999999998
- type: ndcg_at_100 value: 33.79
- type: ndcg_at_1000 value: 39.035
- type: ndcg_at_3 value: 22.845
- type: ndcg_at_5 value: 20.080000000000002
- type: precision_at_1 value: 28.000000000000004
- type: precision_at_10 value: 12.790000000000001
- type: precision_at_100 value: 2.633
- type: precision_at_1000 value: 0.388
- type: precision_at_3 value: 21.367
- type: precision_at_5 value: 17.7
- type: recall_at_1 value: 5.683
- type: recall_at_10 value: 25.91
- type: recall_at_100 value: 53.443
- type: recall_at_1000 value: 78.73
- type: recall_at_3 value: 13.003
- type: recall_at_5 value: 17.932000000000002
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson value: 84.677978681023
- type: cos_sim_spearman value: 83.13093441058189
- type: euclidean_pearson value: 83.35535759341572
- type: euclidean_spearman value: 83.42583744219611
- type: manhattan_pearson value: 83.2243124045889
- type: manhattan_spearman value: 83.39801618652632
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson value: 81.68960206569666
- type: cos_sim_spearman value: 77.3368966488535
- type: euclidean_pearson value: 77.62828980560303
- type: euclidean_spearman value: 76.77951481444651
- type: manhattan_pearson value: 77.88637240839041
- type: manhattan_spearman value: 77.22157841466188
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson value: 84.18745821650724
- type: cos_sim_spearman value: 85.04423285574542
- type: euclidean_pearson value: 85.46604816931023
- type: euclidean_spearman value: 85.5230593932974
- type: manhattan_pearson value: 85.57912805986261
- type: manhattan_spearman value: 85.65955905111873
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson value: 83.6715333300355
- type: cos_sim_spearman value: 82.9058522514908
- type: euclidean_pearson value: 83.9640357424214
- type: euclidean_spearman value: 83.60415457472637
- type: manhattan_pearson value: 84.05621005853469
- type: manhattan_spearman value: 83.87077724707746
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson value: 87.82422928098886
- type: cos_sim_spearman value: 88.12660311894628
- type: euclidean_pearson value: 87.50974805056555
- type: euclidean_spearman value: 87.91957275596677
- type: manhattan_pearson value: 87.74119404878883
- type: manhattan_spearman value: 88.2808922165719
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson value: 84.80605838552093
- type: cos_sim_spearman value: 86.24123388765678
- type: euclidean_pearson value: 85.32648347339814
- type: euclidean_spearman value: 85.60046671950158
- type: manhattan_pearson value: 85.53800168487811
- type: manhattan_spearman value: 85.89542420480763
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson value: 89.87540978988132
- type: cos_sim_spearman value: 90.12715295099461
- type: euclidean_pearson value: 91.61085993525275
- type: euclidean_spearman value: 91.31835942311758
- type: manhattan_pearson value: 91.57500202032934
- type: manhattan_spearman value: 91.1790925526635
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
metrics:
- type: cos_sim_pearson value: 69.87136205329556
- type: cos_sim_spearman value: 68.6253154635078
- type: euclidean_pearson value: 68.91536015034222
- type: euclidean_spearman value: 67.63744649352542
- type: manhattan_pearson value: 69.2000713045275
- type: manhattan_spearman value: 68.16002901587316
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson value: 85.21849551039082
- type: cos_sim_spearman value: 85.6392959372461
- type: euclidean_pearson value: 85.92050852609488
- type: euclidean_spearman value: 85.97205649009734
- type: manhattan_pearson value: 86.1031154802254
- type: manhattan_spearman value: 86.26791155517466
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map value: 86.83953958636627
- type: mrr value: 96.71167612344082
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 64.994
- type: map_at_10 value: 74.763
- type: map_at_100 value: 75.127
- type: map_at_1000 value: 75.143
- type: map_at_3 value: 71.824
- type: map_at_5 value: 73.71
- type: mrr_at_1 value: 68.333
- type: mrr_at_10 value: 75.749
- type: mrr_at_100 value: 75.922
- type: mrr_at_1000 value: 75.938
- type: mrr_at_3 value: 73.556
- type: mrr_at_5 value: 74.739
- type: ndcg_at_1 value: 68.333
- type: ndcg_at_10 value: 79.174
- type: ndcg_at_100 value: 80.41
- type: ndcg_at_1000 value: 80.804
- type: ndcg_at_3 value: 74.361
- type: ndcg_at_5 value: 76.861
- type: precision_at_1 value: 68.333
- type: precision_at_10 value: 10.333
- type: precision_at_100 value: 1.0999999999999999
- type: precision_at_1000 value: 0.11299999999999999
- type: precision_at_3 value: 28.778
- type: precision_at_5 value: 19.067
- type: recall_at_1 value: 64.994
- type: recall_at_10 value: 91.822
- type: recall_at_100 value: 97.0
- type: recall_at_1000 value: 100.0
- type: recall_at_3 value: 78.878
- type: recall_at_5 value: 85.172
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy value: 99.72079207920792
- type: cos_sim_ap value: 93.00265215525152
- type: cos_sim_f1 value: 85.06596306068602
- type: cos_sim_precision value: 90.05586592178771
- type: cos_sim_recall value: 80.60000000000001
- type: dot_accuracy value: 99.66039603960397
- type: dot_ap value: 91.22371407479089
- type: dot_f1 value: 82.34693877551021
- type: dot_precision value: 84.0625
- type: dot_recall value: 80.7
- type: euclidean_accuracy value: 99.71881188118812
- type: euclidean_ap value: 92.88449963304728
- type: euclidean_f1 value: 85.19480519480518
- type: euclidean_precision value: 88.64864864864866
- type: euclidean_recall value: 82.0
- type: manhattan_accuracy value: 99.73267326732673
- type: manhattan_ap value: 93.23055393056883
- type: manhattan_f1 value: 85.88957055214725
- type: manhattan_precision value: 87.86610878661088
- type: manhattan_recall value: 84.0
- type: max_accuracy value: 99.73267326732673
- type: max_ap value: 93.23055393056883
- type: max_f1 value: 85.88957055214725
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure value: 77.3305735900358
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure value: 41.32967136540674
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map value: 55.95514866379359
- type: mrr value: 56.95423245055598
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson value: 30.783007208997144
- type: cos_sim_spearman value: 30.373444721540533
- type: dot_pearson value: 29.210604111143905
- type: dot_spearman value: 29.98809758085659
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 0.234
- type: map_at_10 value: 1.894
- type: map_at_100 value: 1.894
- type: map_at_1000 value: 1.894
- type: map_at_3 value: 0.636
- type: map_at_5 value: 1.0
- type: mrr_at_1 value: 88.0
- type: mrr_at_10 value: 93.667
- type: mrr_at_100 value: 93.667
- type: mrr_at_1000 value: 93.667
- type: mrr_at_3 value: 93.667
- type: mrr_at_5 value: 93.667
- type: ndcg_at_1 value: 85.0
- type: ndcg_at_10 value: 74.798
- type: ndcg_at_100 value: 16.462
- type: ndcg_at_1000 value: 7.0889999999999995
- type: ndcg_at_3 value: 80.754
- type: ndcg_at_5 value: 77.319
- type: precision_at_1 value: 88.0
- type: precision_at_10 value: 78.0
- type: precision_at_100 value: 7.8
- type: precision_at_1000 value: 0.7799999999999999
- type: precision_at_3 value: 83.333
- type: precision_at_5 value: 80.80000000000001
- type: recall_at_1 value: 0.234
- type: recall_at_10 value: 2.093
- type: recall_at_100 value: 2.093
- type: recall_at_1000 value: 2.093
- type: recall_at_3 value: 0.662
- type: recall_at_5 value: 1.0739999999999998
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 2.703
- type: map_at_10 value: 10.866000000000001
- type: map_at_100 value: 10.866000000000001
- type: map_at_1000 value: 10.866000000000001
- type: map_at_3 value: 5.909
- type: map_at_5 value: 7.35
- type: mrr_at_1 value: 36.735
- type: mrr_at_10 value: 53.583000000000006
- type: mrr_at_100 value: 53.583000000000006
- type: mrr_at_1000 value: 53.583000000000006
- type: mrr_at_3 value: 49.32
- type: mrr_at_5 value: 51.769
- type: ndcg_at_1 value: 34.694
- type: ndcg_at_10 value: 27.926000000000002
- type: ndcg_at_100 value: 22.701
- type: ndcg_at_1000 value: 22.701
- type: ndcg_at_3 value: 32.073
- type: ndcg_at_5 value: 28.327999999999996
- type: precision_at_1 value: 36.735
- type: precision_at_10 value: 24.694
- type: precision_at_100 value: 2.469
- type: precision_at_1000 value: 0.247
- type: precision_at_3 value: 31.973000000000003
- type: precision_at_5 value: 26.939
- type: recall_at_1 value: 2.703
- type: recall_at_10 value: 17.702
- type: recall_at_100 value: 17.702
- type: recall_at_1000 value: 17.702
- type: recall_at_3 value: 7.208
- type: recall_at_5 value: 9.748999999999999
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy value: 70.79960000000001
- type: ap value: 15.467565415565815
- type: f1 value: 55.28639823443618
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy value: 64.7792869269949
- type: f1 value: 65.08597154774318
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure value: 55.70352297774293
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy value: 88.27561542588067
- type: cos_sim_ap value: 81.08262141256193
- type: cos_sim_f1 value: 73.82341501361338
- type: cos_sim_precision value: 72.5720112159062
- type: cos_sim_recall value: 75.11873350923483
- type: dot_accuracy value: 86.66030875603504
- type: dot_ap value: 76.6052349228621
- type: dot_f1 value: 70.13897280966768
- type: dot_precision value: 64.70457079152732
- type: dot_recall value: 76.56992084432717
- type: euclidean_accuracy value: 88.37098408535495
- type: euclidean_ap value: 81.12515230092113
- type: euclidean_f1 value: 74.10338225909379
- type: euclidean_precision value: 71.76761433868974
- type: euclidean_recall value: 76.59630606860158
- type: manhattan_accuracy value: 88.34118137926924
- type: manhattan_ap value: 80.95751834536561
- type: manhattan_f1 value: 73.9119496855346
- type: manhattan_precision value: 70.625
- type: manhattan_recall value: 77.5197889182058
- type: max_accuracy value: 88.37098408535495
- type: max_ap value: 81.12515230092113
- type: max_f1 value: 74.10338225909379
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy value: 89.79896767182831
- type: cos_sim_ap value: 87.40071784061065
- type: cos_sim_f1 value: 79.87753144712087
- type: cos_sim_precision value: 76.67304015296367
- type: cos_sim_recall value: 83.3615645210964
- type: dot_accuracy value: 88.95486474948578
- type: dot_ap value: 86.00227979119943
- type: dot_f1 value: 78.54601474525914
- type: dot_precision value: 75.00525394045535
- type: dot_recall value: 82.43763473975977
- type: euclidean_accuracy value: 89.7892653393876
- type: euclidean_ap value: 87.42174706480819
- type: euclidean_f1 value: 80.07283321194465
- type: euclidean_precision value: 75.96738529574351
- type: euclidean_recall value: 84.6473668001232
- type: manhattan_accuracy value: 89.8474793340319
- type: manhattan_ap value: 87.47814292587448
- type: manhattan_f1 value: 80.15461150280949
- type: manhattan_precision value: 74.88798234468
- type: manhattan_recall value: 86.21804742839544
- type: max_accuracy value: 89.8474793340319
- type: max_ap value: 87.47814292587448
- type: max_f1 value: 80.15461150280949
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
Model Summary
GritLM is a generative representational instruction tuned language model. It unifies text representation (embedding) and text generation into a single model achieving state-of-the-art performance on both types of tasks.
- Repository: ContextualAI/gritlm
- Paper: https://arxiv.org/abs/2402.09906
- Logs: https://wandb.ai/muennighoff/gritlm/runs/0uui712t/overview
- Script: https://github.com/ContextualAI/gritlm/blob/main/scripts/training/train_gritlm_7b.sh
| Model | Description |
|---|---|
| GritLM 7B | Mistral 7B finetuned using GRIT |
| GritLM 8x7B | Mixtral 8x7B finetuned using GRIT |
Use
The model usage is documented here.
Citation
@misc{muennighoff2024generative,
title={Generative Representational Instruction Tuning},
author={Niklas Muennighoff and Hongjin Su and Liang Wang and Nan Yang and Furu Wei and Tao Yu and Amanpreet Singh and Douwe Kiela},
year={2024},
eprint={2402.09906},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
- Task
- Text Generation
- Library
- transformers
- Type
- mistral
- Created
- May 3, 2024
- Updated
- May 3, 2024