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README.md

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+---
+tags:
+- mteb
+- llama-cpp
+- gguf-my-repo
+base_model: Classical/Yinka
+model-index:
+- name: checkpoint-1431
+  results:
+  - task:
+      type: STS
+    dataset:
+      name: MTEB AFQMC
+      type: C-MTEB/AFQMC
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 56.306314279047875
+    - type: cos_sim_spearman
+      value: 61.020227685004016
+    - type: euclidean_pearson
+      value: 58.61821670933433
+    - type: euclidean_spearman
+      value: 60.131457106640674
+    - type: manhattan_pearson
+      value: 58.6189460369694
+    - type: manhattan_spearman
+      value: 60.126350618526224
+  - task:
+      type: STS
+    dataset:
+      name: MTEB ATEC
+      type: C-MTEB/ATEC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 55.8612958476143
+    - type: cos_sim_spearman
+      value: 59.01977664864512
+    - type: euclidean_pearson
+      value: 62.028094897243655
+    - type: euclidean_spearman
+      value: 58.6046814257705
+    - type: manhattan_pearson
+      value: 62.02580042431887
+    - type: manhattan_spearman
+      value: 58.60626890004892
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonReviewsClassification (zh)
+      type: mteb/amazon_reviews_multi
+      config: zh
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 49.496
+    - type: f1
+      value: 46.673963383873065
+  - task:
+      type: STS
+    dataset:
+      name: MTEB BQ
+      type: C-MTEB/BQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 70.73971622592535
+    - type: cos_sim_spearman
+      value: 72.76102992060764
+    - type: euclidean_pearson
+      value: 71.04525865868672
+    - type: euclidean_spearman
+      value: 72.4032852155075
+    - type: manhattan_pearson
+      value: 71.03693009336658
+    - type: manhattan_spearman
+      value: 72.39635701224252
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB CLSClusteringP2P
+      type: C-MTEB/CLSClusteringP2P
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 56.34751074520767
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB CLSClusteringS2S
+      type: C-MTEB/CLSClusteringS2S
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 48.4856662121073
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB CMedQAv1
+      type: C-MTEB/CMedQAv1-reranking
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map
+      value: 89.26384109024997
+    - type: mrr
+      value: 91.27261904761905
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB CMedQAv2
+      type: C-MTEB/CMedQAv2-reranking
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map
+      value: 90.0464058154547
+    - type: mrr
+      value: 92.06480158730159
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CmedqaRetrieval
+      type: C-MTEB/CmedqaRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.236
+    - type: map_at_10
+      value: 40.778
+    - type: map_at_100
+      value: 42.692
+    - type: map_at_1000
+      value: 42.787
+    - type: map_at_3
+      value: 36.362
+    - type: map_at_5
+      value: 38.839
+    - type: mrr_at_1
+      value: 41.335
+    - type: mrr_at_10
+      value: 49.867
+    - type: mrr_at_100
+      value: 50.812999999999995
+    - type: mrr_at_1000
+      value: 50.848000000000006
+    - type: mrr_at_3
+      value: 47.354
+    - type: mrr_at_5
+      value: 48.718
+    - type: ndcg_at_1
+      value: 41.335
+    - type: ndcg_at_10
+      value: 47.642
+    - type: ndcg_at_100
+      value: 54.855
+    - type: ndcg_at_1000
+      value: 56.449000000000005
+    - type: ndcg_at_3
+      value: 42.203
+    - type: ndcg_at_5
+      value: 44.416
+    - type: precision_at_1
+      value: 41.335
+    - type: precision_at_10
+      value: 10.568
+    - type: precision_at_100
+      value: 1.6400000000000001
+    - type: precision_at_1000
+      value: 0.184
+    - type: precision_at_3
+      value: 23.998
+    - type: precision_at_5
+      value: 17.389
+    - type: recall_at_1
+      value: 27.236
+    - type: recall_at_10
+      value: 58.80800000000001
+    - type: recall_at_100
+      value: 88.411
+    - type: recall_at_1000
+      value: 99.032
+    - type: recall_at_3
+      value: 42.253
+    - type: recall_at_5
+      value: 49.118
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB Cmnli
+      type: C-MTEB/CMNLI
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 86.03728202044498
+    - type: cos_sim_ap
+      value: 92.49469583272597
+    - type: cos_sim_f1
+      value: 86.74095974528088
+    - type: cos_sim_precision
+      value: 84.43657294664601
+    - type: cos_sim_recall
+      value: 89.17465513210195
+    - type: dot_accuracy
+      value: 72.21888153938664
+    - type: dot_ap
+      value: 80.59377163340332
+    - type: dot_f1
+      value: 74.96686040583258
+    - type: dot_precision
+      value: 66.4737793851718
+    - type: dot_recall
+      value: 85.94809445873275
+    - type: euclidean_accuracy
+      value: 85.47203848466627
+    - type: euclidean_ap
+      value: 91.89152584749868
+    - type: euclidean_f1
+      value: 86.38105975197294
+    - type: euclidean_precision
+      value: 83.40953625081646
+    - type: euclidean_recall
+      value: 89.5721299976619
+    - type: manhattan_accuracy
+      value: 85.3758268190018
+    - type: manhattan_ap
+      value: 91.88989707722311
+    - type: manhattan_f1
+      value: 86.39767519839052
+    - type: manhattan_precision
+      value: 82.76231263383298
+    - type: manhattan_recall
+      value: 90.36707972878185
+    - type: max_accuracy
+      value: 86.03728202044498
+    - type: max_ap
+      value: 92.49469583272597
+    - type: max_f1
+      value: 86.74095974528088
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CovidRetrieval
+      type: C-MTEB/CovidRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 74.34100000000001
+    - type: map_at_10
+      value: 82.49499999999999
+    - type: map_at_100
+      value: 82.64200000000001
+    - type: map_at_1000
+      value: 82.643
+    - type: map_at_3
+      value: 81.142
+    - type: map_at_5
+      value: 81.95400000000001
+    - type: mrr_at_1
+      value: 74.71
+    - type: mrr_at_10
+      value: 82.553
+    - type: mrr_at_100
+      value: 82.699
+    - type: mrr_at_1000
+      value: 82.70100000000001
+    - type: mrr_at_3
+      value: 81.279
+    - type: mrr_at_5
+      value: 82.069
+    - type: ndcg_at_1
+      value: 74.605
+    - type: ndcg_at_10
+      value: 85.946
+    - type: ndcg_at_100
+      value: 86.607
+    - type: ndcg_at_1000
+      value: 86.669
+    - type: ndcg_at_3
+      value: 83.263
+    - type: ndcg_at_5
+      value: 84.71600000000001
+    - type: precision_at_1
+      value: 74.605
+    - type: precision_at_10
+      value: 9.758
+    - type: precision_at_100
+      value: 1.005
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_3
+      value: 29.996000000000002
+    - type: precision_at_5
+      value: 18.736
+    - type: recall_at_1
+      value: 74.34100000000001
+    - type: recall_at_10
+      value: 96.523
+    - type: recall_at_100
+      value: 99.473
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 89.278
+    - type: recall_at_5
+      value: 92.83500000000001
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB DuRetrieval
+      type: C-MTEB/DuRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.950000000000003
+    - type: map_at_10
+      value: 82.408
+    - type: map_at_100
+      value: 85.057
+    - type: map_at_1000
+      value: 85.09100000000001
+    - type: map_at_3
+      value: 57.635999999999996
+    - type: map_at_5
+      value: 72.48
+    - type: mrr_at_1
+      value: 92.15
+    - type: mrr_at_10
+      value: 94.554
+    - type: mrr_at_100
+      value: 94.608
+    - type: mrr_at_1000
+      value: 94.61
+    - type: mrr_at_3
+      value: 94.292
+    - type: mrr_at_5
+      value: 94.459
+    - type: ndcg_at_1
+      value: 92.15
+    - type: ndcg_at_10
+      value: 89.108
+    - type: ndcg_at_100
+      value: 91.525
+    - type: ndcg_at_1000
+      value: 91.82900000000001
+    - type: ndcg_at_3
+      value: 88.44
+    - type: ndcg_at_5
+      value: 87.271
+    - type: precision_at_1
+      value: 92.15
+    - type: precision_at_10
+      value: 42.29
+    - type: precision_at_100
+      value: 4.812
+    - type: precision_at_1000
+      value: 0.48900000000000005
+    - type: precision_at_3
+      value: 79.14999999999999
+    - type: precision_at_5
+      value: 66.64
+    - type: recall_at_1
+      value: 26.950000000000003
+    - type: recall_at_10
+      value: 89.832
+    - type: recall_at_100
+      value: 97.921
+    - type: recall_at_1000
+      value: 99.471
+    - type: recall_at_3
+      value: 59.562000000000005
+    - type: recall_at_5
+      value: 76.533
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB EcomRetrieval
+      type: C-MTEB/EcomRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 53.5
+    - type: map_at_10
+      value: 63.105999999999995
+    - type: map_at_100
+      value: 63.63100000000001
+    - type: map_at_1000
+      value: 63.641999999999996
+    - type: map_at_3
+      value: 60.617
+    - type: map_at_5
+      value: 62.132
+    - type: mrr_at_1
+      value: 53.5
+    - type: mrr_at_10
+      value: 63.105999999999995
+    - type: mrr_at_100
+      value: 63.63100000000001
+    - type: mrr_at_1000
+      value: 63.641999999999996
+    - type: mrr_at_3
+      value: 60.617
+    - type: mrr_at_5
+      value: 62.132
+    - type: ndcg_at_1
+      value: 53.5
+    - type: ndcg_at_10
+      value: 67.92200000000001
+    - type: ndcg_at_100
+      value: 70.486
+    - type: ndcg_at_1000
+      value: 70.777
+    - type: ndcg_at_3
+      value: 62.853
+    - type: ndcg_at_5
+      value: 65.59899999999999
+    - type: precision_at_1
+      value: 53.5
+    - type: precision_at_10
+      value: 8.309999999999999
+    - type: precision_at_100
+      value: 0.951
+    - type: precision_at_1000
+      value: 0.097
+    - type: precision_at_3
+      value: 23.1
+    - type: precision_at_5
+      value: 15.2
+    - type: recall_at_1
+      value: 53.5
+    - type: recall_at_10
+      value: 83.1
+    - type: recall_at_100
+      value: 95.1
+    - type: recall_at_1000
+      value: 97.39999999999999
+    - type: recall_at_3
+      value: 69.3
+    - type: recall_at_5
+      value: 76.0
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB IFlyTek
+      type: C-MTEB/IFlyTek-classification
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 51.773759138130046
+    - type: f1
+      value: 40.38600802756481
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB JDReview
+      type: C-MTEB/JDReview-classification
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 88.48030018761726
+    - type: ap
+      value: 59.2732541555627
+    - type: f1
+      value: 83.58836007358619
+  - task:
+      type: STS
+    dataset:
+      name: MTEB LCQMC
+      type: C-MTEB/LCQMC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 73.67511194245922
+    - type: cos_sim_spearman
+      value: 79.43347759067298
+    - type: euclidean_pearson
+      value: 79.04491504318766
+    - type: euclidean_spearman
+      value: 79.14478545356785
+    - type: manhattan_pearson
+      value: 79.03365022867428
+    - type: manhattan_spearman
+      value: 79.13172717619908
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MMarcoRetrieval
+      type: C-MTEB/MMarcoRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 67.184
+    - type: map_at_10
+      value: 76.24600000000001
+    - type: map_at_100
+      value: 76.563
+    - type: map_at_1000
+      value: 76.575
+    - type: map_at_3
+      value: 74.522
+    - type: map_at_5
+      value: 75.598
+    - type: mrr_at_1
+      value: 69.47
+    - type: mrr_at_10
+      value: 76.8
+    - type: mrr_at_100
+      value: 77.082
+    - type: mrr_at_1000
+      value: 77.093
+    - type: mrr_at_3
+      value: 75.29400000000001
+    - type: mrr_at_5
+      value: 76.24
+    - type: ndcg_at_1
+      value: 69.47
+    - type: ndcg_at_10
+      value: 79.81099999999999
+    - type: ndcg_at_100
+      value: 81.187
+    - type: ndcg_at_1000
+      value: 81.492
+    - type: ndcg_at_3
+      value: 76.536
+    - type: ndcg_at_5
+      value: 78.367
+    - type: precision_at_1
+      value: 69.47
+    - type: precision_at_10
+      value: 9.599
+    - type: precision_at_100
+      value: 1.026
+    - type: precision_at_1000
+      value: 0.105
+    - type: precision_at_3
+      value: 28.777
+    - type: precision_at_5
+      value: 18.232
+    - type: recall_at_1
+      value: 67.184
+    - type: recall_at_10
+      value: 90.211
+    - type: recall_at_100
+      value: 96.322
+    - type: recall_at_1000
+      value: 98.699
+    - type: recall_at_3
+      value: 81.556
+    - type: recall_at_5
+      value: 85.931
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveIntentClassification (zh-CN)
+      type: mteb/amazon_massive_intent
+      config: zh-CN
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 76.96032279757901
+    - type: f1
+      value: 73.48052314033545
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveScenarioClassification (zh-CN)
+      type: mteb/amazon_massive_scenario
+      config: zh-CN
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 84.64357767316744
+    - type: f1
+      value: 83.58250539497922
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MedicalRetrieval
+      type: C-MTEB/MedicalRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 56.00000000000001
+    - type: map_at_10
+      value: 62.066
+    - type: map_at_100
+      value: 62.553000000000004
+    - type: map_at_1000
+      value: 62.598
+    - type: map_at_3
+      value: 60.4
+    - type: map_at_5
+      value: 61.370000000000005
+    - type: mrr_at_1
+      value: 56.2
+    - type: mrr_at_10
+      value: 62.166
+    - type: mrr_at_100
+      value: 62.653000000000006
+    - type: mrr_at_1000
+      value: 62.699000000000005
+    - type: mrr_at_3
+      value: 60.5
+    - type: mrr_at_5
+      value: 61.47
+    - type: ndcg_at_1
+      value: 56.00000000000001
+    - type: ndcg_at_10
+      value: 65.199
+    - type: ndcg_at_100
+      value: 67.79899999999999
+    - type: ndcg_at_1000
+      value: 69.056
+    - type: ndcg_at_3
+      value: 61.814
+    - type: ndcg_at_5
+      value: 63.553000000000004
+    - type: precision_at_1
+      value: 56.00000000000001
+    - type: precision_at_10
+      value: 7.51
+    - type: precision_at_100
+      value: 0.878
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 21.967
+    - type: precision_at_5
+      value: 14.02
+    - type: recall_at_1
+      value: 56.00000000000001
+    - type: recall_at_10
+      value: 75.1
+    - type: recall_at_100
+      value: 87.8
+    - type: recall_at_1000
+      value: 97.7
+    - type: recall_at_3
+      value: 65.9
+    - type: recall_at_5
+      value: 70.1
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB MMarcoReranking
+      type: C-MTEB/Mmarco-reranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 32.74158258279793
+    - type: mrr
+      value: 31.56071428571428
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MultilingualSentiment
+      type: C-MTEB/MultilingualSentiment-classification
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 78.96666666666667
+    - type: f1
+      value: 78.82528563818045
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB Ocnli
+      type: C-MTEB/OCNLI
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 83.54087709799674
+    - type: cos_sim_ap
+      value: 87.26170197077586
+    - type: cos_sim_f1
+      value: 84.7609561752988
+    - type: cos_sim_precision
+      value: 80.20735155513667
+    - type: cos_sim_recall
+      value: 89.86272439281943
+    - type: dot_accuracy
+      value: 72.22523010286952
+    - type: dot_ap
+      value: 79.51975358187732
+    - type: dot_f1
+      value: 76.32183908045977
+    - type: dot_precision
+      value: 67.58957654723126
+    - type: dot_recall
+      value: 87.64519535374869
+    - type: euclidean_accuracy
+      value: 82.0249052517596
+    - type: euclidean_ap
+      value: 85.32829948726406
+    - type: euclidean_f1
+      value: 83.24924318869829
+    - type: euclidean_precision
+      value: 79.71014492753623
+    - type: euclidean_recall
+      value: 87.11721224920802
+    - type: manhattan_accuracy
+      value: 82.13318895506227
+    - type: manhattan_ap
+      value: 85.28856869288006
+    - type: manhattan_f1
+      value: 83.34946757018393
+    - type: manhattan_precision
+      value: 76.94369973190348
+    - type: manhattan_recall
+      value: 90.91869060190075
+    - type: max_accuracy
+      value: 83.54087709799674
+    - type: max_ap
+      value: 87.26170197077586
+    - type: max_f1
+      value: 84.7609561752988
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB OnlineShopping
+      type: C-MTEB/OnlineShopping-classification
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 94.56
+    - type: ap
+      value: 92.80848436710805
+    - type: f1
+      value: 94.54951966576111
+  - task:
+      type: STS
+    dataset:
+      name: MTEB PAWSX
+      type: C-MTEB/PAWSX
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 39.0866558287863
+    - type: cos_sim_spearman
+      value: 45.9211126233312
+    - type: euclidean_pearson
+      value: 44.86568743222145
+    - type: euclidean_spearman
+      value: 45.63882757207507
+    - type: manhattan_pearson
+      value: 44.89480036909126
+    - type: manhattan_spearman
+      value: 45.65929449046206
+  - task:
+      type: STS
+    dataset:
+      name: MTEB QBQTC
+      type: C-MTEB/QBQTC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 43.04701793979569
+    - type: cos_sim_spearman
+      value: 44.87491033760315
+    - type: euclidean_pearson
+      value: 36.2004061032567
+    - type: euclidean_spearman
+      value: 41.44823909683865
+    - type: manhattan_pearson
+      value: 36.136113427955095
+    - type: manhattan_spearman
+      value: 41.39225495993949
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS22 (zh)
+      type: mteb/sts22-crosslingual-sts
+      config: zh
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 61.65611315777857
+    - type: cos_sim_spearman
+      value: 64.4067673105648
+    - type: euclidean_pearson
+      value: 61.814977248797184
+    - type: euclidean_spearman
+      value: 63.99473350700169
+    - type: manhattan_pearson
+      value: 61.684304629588624
+    - type: manhattan_spearman
+      value: 63.97831213239316
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STSB
+      type: C-MTEB/STSB
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 76.57324933064379
+    - type: cos_sim_spearman
+      value: 79.23602286949782
+    - type: euclidean_pearson
+      value: 80.28226284310948
+    - type: euclidean_spearman
+      value: 80.32210477608423
+    - type: manhattan_pearson
+      value: 80.27262188617811
+    - type: manhattan_spearman
+      value: 80.31619185039723
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB T2Reranking
+      type: C-MTEB/T2Reranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 67.05266891356277
+    - type: mrr
+      value: 77.1906333623497
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB T2Retrieval
+      type: C-MTEB/T2Retrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.212
+    - type: map_at_10
+      value: 78.932
+    - type: map_at_100
+      value: 82.51899999999999
+    - type: map_at_1000
+      value: 82.575
+    - type: map_at_3
+      value: 55.614
+    - type: map_at_5
+      value: 68.304
+    - type: mrr_at_1
+      value: 91.211
+    - type: mrr_at_10
+      value: 93.589
+    - type: mrr_at_100
+      value: 93.659
+    - type: mrr_at_1000
+      value: 93.662
+    - type: mrr_at_3
+      value: 93.218
+    - type: mrr_at_5
+      value: 93.453
+    - type: ndcg_at_1
+      value: 91.211
+    - type: ndcg_at_10
+      value: 86.24000000000001
+    - type: ndcg_at_100
+      value: 89.614
+    - type: ndcg_at_1000
+      value: 90.14
+    - type: ndcg_at_3
+      value: 87.589
+    - type: ndcg_at_5
+      value: 86.265
+    - type: precision_at_1
+      value: 91.211
+    - type: precision_at_10
+      value: 42.626
+    - type: precision_at_100
+      value: 5.043
+    - type: precision_at_1000
+      value: 0.517
+    - type: precision_at_3
+      value: 76.42
+    - type: precision_at_5
+      value: 64.045
+    - type: recall_at_1
+      value: 28.212
+    - type: recall_at_10
+      value: 85.223
+    - type: recall_at_100
+      value: 96.229
+    - type: recall_at_1000
+      value: 98.849
+    - type: recall_at_3
+      value: 57.30800000000001
+    - type: recall_at_5
+      value: 71.661
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB TNews
+      type: C-MTEB/TNews-classification
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 54.385000000000005
+    - type: f1
+      value: 52.38762400903556
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ThuNewsClusteringP2P
+      type: C-MTEB/ThuNewsClusteringP2P
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 74.55283855942916
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ThuNewsClusteringS2S
+      type: C-MTEB/ThuNewsClusteringS2S
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 68.55115316700493
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB VideoRetrieval
+      type: C-MTEB/VideoRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 58.8
+    - type: map_at_10
+      value: 69.035
+    - type: map_at_100
+      value: 69.52000000000001
+    - type: map_at_1000
+      value: 69.529
+    - type: map_at_3
+      value: 67.417
+    - type: map_at_5
+      value: 68.407
+    - type: mrr_at_1
+      value: 58.8
+    - type: mrr_at_10
+      value: 69.035
+    - type: mrr_at_100
+      value: 69.52000000000001
+    - type: mrr_at_1000
+      value: 69.529
+    - type: mrr_at_3
+      value: 67.417
+    - type: mrr_at_5
+      value: 68.407
+    - type: ndcg_at_1
+      value: 58.8
+    - type: ndcg_at_10
+      value: 73.395
+    - type: ndcg_at_100
+      value: 75.62
+    - type: ndcg_at_1000
+      value: 75.90299999999999
+    - type: ndcg_at_3
+      value: 70.11800000000001
+    - type: ndcg_at_5
+      value: 71.87400000000001
+    - type: precision_at_1
+      value: 58.8
+    - type: precision_at_10
+      value: 8.68
+    - type: precision_at_100
+      value: 0.9690000000000001
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_3
+      value: 25.967000000000002
+    - type: precision_at_5
+      value: 16.42
+    - type: recall_at_1
+      value: 58.8
+    - type: recall_at_10
+      value: 86.8
+    - type: recall_at_100
+      value: 96.89999999999999
+    - type: recall_at_1000
+      value: 99.2
+    - type: recall_at_3
+      value: 77.9
+    - type: recall_at_5
+      value: 82.1
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB Waimai
+      type: C-MTEB/waimai-classification
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 89.42
+    - type: ap
+      value: 75.35978503182068
+    - type: f1
+      value: 88.01006394348263
+---
+
+# jimi0209/Yinka-Q5_K_M-GGUF
+This model was converted to GGUF format from [`Classical/Yinka`](https://huggingface.co/Classical/Yinka) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
+Refer to the [original model card](https://huggingface.co/Classical/Yinka) for more details on the model.
+
+## Use with llama.cpp
+Install llama.cpp through brew (works on Mac and Linux)
+
+```bash
+brew install llama.cpp
+
+```
+Invoke the llama.cpp server or the CLI.
+
+### CLI:
+```bash
+llama-cli --hf-repo jimi0209/Yinka-Q5_K_M-GGUF --hf-file yinka-q5_k_m.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo jimi0209/Yinka-Q5_K_M-GGUF --hf-file yinka-q5_k_m.gguf -c 2048
+```
+
+Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
+
+Step 1: Clone llama.cpp from GitHub.
+```
+git clone https://github.com/ggerganov/llama.cpp
+```
+
+Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
+```
+cd llama.cpp && LLAMA_CURL=1 make
+```
+
+Step 3: Run inference through the main binary.
+```
+./llama-cli --hf-repo jimi0209/Yinka-Q5_K_M-GGUF --hf-file yinka-q5_k_m.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo jimi0209/Yinka-Q5_K_M-GGUF --hf-file yinka-q5_k_m.gguf -c 2048
+```