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--- |
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license: mit |
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base_model: croissantllm/CroissantCool-v0.2 |
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datasets: asi/wikitext_fr |
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tags: |
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- generated_from_trainer |
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- mteb |
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metrics: |
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- accuracy |
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model-index: |
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- name: final |
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results: |
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- task: |
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type: Clustering |
|
dataset: |
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type: lyon-nlp/alloprof |
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name: MTEB AlloProfClusteringP2P (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b |
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metrics: |
|
- type: v_measure |
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value: 62.345943052433995 |
|
- task: |
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type: Clustering |
|
dataset: |
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type: lyon-nlp/alloprof |
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name: MTEB AlloProfClusteringS2S (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b |
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metrics: |
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- type: v_measure |
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value: 25.729454984521148 |
|
- task: |
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type: Reranking |
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dataset: |
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type: lyon-nlp/mteb-fr-reranking-alloprof-s2p |
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name: MTEB AlloprofReranking (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: 65393d0d7a08a10b4e348135e824f385d420b0fd |
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metrics: |
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- type: map |
|
value: 26.596323297349183 |
|
- type: mrr |
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value: 26.091629657044162 |
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- task: |
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type: Retrieval |
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dataset: |
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type: lyon-nlp/alloprof |
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name: MTEB AlloprofRetrieval (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: fcf295ea64c750f41fadbaa37b9b861558e1bfbd |
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metrics: |
|
- type: map_at_1 |
|
value: 0.345 |
|
- type: map_at_10 |
|
value: 0.9339999999999999 |
|
- type: map_at_100 |
|
value: 1.191 |
|
- type: map_at_1000 |
|
value: 1.3419999999999999 |
|
- type: map_at_20 |
|
value: 1.02 |
|
- type: map_at_3 |
|
value: 0.6689999999999999 |
|
- type: map_at_5 |
|
value: 0.753 |
|
- type: mrr_at_1 |
|
value: 0.345 |
|
- type: mrr_at_10 |
|
value: 0.9339999999999999 |
|
- type: mrr_at_100 |
|
value: 1.191 |
|
- type: mrr_at_1000 |
|
value: 1.3419999999999999 |
|
- type: mrr_at_20 |
|
value: 1.02 |
|
- type: mrr_at_3 |
|
value: 0.6689999999999999 |
|
- type: mrr_at_5 |
|
value: 0.753 |
|
- type: ndcg_at_1 |
|
value: 0.345 |
|
- type: ndcg_at_10 |
|
value: 1.384 |
|
- type: ndcg_at_100 |
|
value: 3.1510000000000002 |
|
- type: ndcg_at_1000 |
|
value: 9.014 |
|
- type: ndcg_at_20 |
|
value: 1.6920000000000002 |
|
- type: ndcg_at_3 |
|
value: 0.7849999999999999 |
|
- type: ndcg_at_5 |
|
value: 0.941 |
|
- type: precision_at_1 |
|
value: 0.345 |
|
- type: precision_at_10 |
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value: 0.28900000000000003 |
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- type: precision_at_100 |
|
value: 0.124 |
|
- type: precision_at_1000 |
|
value: 0.063 |
|
- type: precision_at_20 |
|
value: 0.20500000000000002 |
|
- type: precision_at_3 |
|
value: 0.374 |
|
- type: precision_at_5 |
|
value: 0.302 |
|
- type: recall_at_1 |
|
value: 0.345 |
|
- type: recall_at_10 |
|
value: 2.8930000000000002 |
|
- type: recall_at_100 |
|
value: 12.435 |
|
- type: recall_at_1000 |
|
value: 62.867 |
|
- type: recall_at_20 |
|
value: 4.102 |
|
- type: recall_at_3 |
|
value: 1.123 |
|
- type: recall_at_5 |
|
value: 1.5110000000000001 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_reviews_multi |
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name: MTEB AmazonReviewsClassification (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
|
- type: accuracy |
|
value: 32.662 |
|
- type: f1 |
|
value: 32.443152253731846 |
|
- task: |
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type: Retrieval |
|
dataset: |
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type: maastrichtlawtech/bsard |
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name: MTEB BSARDRetrieval (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59 |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.0 |
|
- type: map_at_10 |
|
value: 0.0 |
|
- type: map_at_100 |
|
value: 0.062 |
|
- type: map_at_1000 |
|
value: 0.077 |
|
- type: map_at_20 |
|
value: 0.0 |
|
- type: map_at_3 |
|
value: 0.0 |
|
- type: map_at_5 |
|
value: 0.0 |
|
- type: mrr_at_1 |
|
value: 0.0 |
|
- type: mrr_at_10 |
|
value: 0.0 |
|
- type: mrr_at_100 |
|
value: 0.062 |
|
- type: mrr_at_1000 |
|
value: 0.077 |
|
- type: mrr_at_20 |
|
value: 0.0 |
|
- type: mrr_at_3 |
|
value: 0.0 |
|
- type: mrr_at_5 |
|
value: 0.0 |
|
- type: ndcg_at_1 |
|
value: 0.0 |
|
- type: ndcg_at_10 |
|
value: 0.0 |
|
- type: ndcg_at_100 |
|
value: 0.484 |
|
- type: ndcg_at_1000 |
|
value: 1.054 |
|
- type: ndcg_at_20 |
|
value: 0.0 |
|
- type: ndcg_at_3 |
|
value: 0.0 |
|
- type: ndcg_at_5 |
|
value: 0.0 |
|
- type: precision_at_1 |
|
value: 0.0 |
|
- type: precision_at_10 |
|
value: 0.0 |
|
- type: precision_at_100 |
|
value: 0.027 |
|
- type: precision_at_1000 |
|
value: 0.008 |
|
- type: precision_at_20 |
|
value: 0.0 |
|
- type: precision_at_3 |
|
value: 0.0 |
|
- type: precision_at_5 |
|
value: 0.0 |
|
- type: recall_at_1 |
|
value: 0.0 |
|
- type: recall_at_10 |
|
value: 0.0 |
|
- type: recall_at_100 |
|
value: 2.703 |
|
- type: recall_at_1000 |
|
value: 7.6579999999999995 |
|
- type: recall_at_20 |
|
value: 0.0 |
|
- type: recall_at_3 |
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value: 0.0 |
|
- type: recall_at_5 |
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value: 0.0 |
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- task: |
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type: Clustering |
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dataset: |
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type: lyon-nlp/clustering-hal-s2s |
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name: MTEB HALClusteringS2S (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915 |
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metrics: |
|
- type: v_measure |
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value: 13.77084465510841 |
|
- task: |
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type: Clustering |
|
dataset: |
|
type: mlsum |
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name: MTEB MLSUMClusteringP2P (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 |
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metrics: |
|
- type: v_measure |
|
value: 45.43375637260015 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mlsum |
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name: MTEB MLSUMClusteringS2S (fra-Latn) |
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config: fra-Latn |
|
split: test |
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revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 |
|
metrics: |
|
- type: v_measure |
|
value: 45.20564648796975 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
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name: MTEB MTOPDomainClassification (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 73.42937676166615 |
|
- type: f1 |
|
value: 72.65861284500563 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
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name: MTEB MTOPIntentClassification (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 58.54368932038836 |
|
- type: f1 |
|
value: 37.51985447597095 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/masakhanews |
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name: MTEB MasakhaNEWSClassification (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: 18193f187b92da67168c655c9973a165ed9593dd |
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metrics: |
|
- type: accuracy |
|
value: 75.56872037914692 |
|
- type: f1 |
|
value: 71.99185345982795 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: masakhane/masakhanews |
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name: MTEB MasakhaNEWSClusteringP2P (fra-Latn) |
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config: fra-Latn |
|
split: test |
|
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 |
|
metrics: |
|
- type: v_measure |
|
value: 38.20382948117535 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: masakhane/masakhanews |
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name: MTEB MasakhaNEWSClusteringS2S (fra-Latn) |
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config: fra-Latn |
|
split: test |
|
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 |
|
metrics: |
|
- type: v_measure |
|
value: 26.943825642352117 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (fra-Latn) |
|
config: fra-Latn |
|
split: test |
|
revision: 4672e20407010da34463acc759c162ca9734bca6 |
|
metrics: |
|
- type: accuracy |
|
value: 50.20847343644924 |
|
- type: f1 |
|
value: 47.32281768380685 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (fra-Latn) |
|
config: fra-Latn |
|
split: test |
|
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8 |
|
metrics: |
|
- type: accuracy |
|
value: 52.57565568258238 |
|
- type: f1 |
|
value: 50.95953249242336 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: jinaai/mintakaqa |
|
name: MTEB MintakaRetrieval (fra-Latn) |
|
config: fra-Latn |
|
split: test |
|
revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.164 |
|
- type: map_at_10 |
|
value: 0.584 |
|
- type: map_at_100 |
|
value: 0.8240000000000001 |
|
- type: map_at_1000 |
|
value: 0.9769999999999999 |
|
- type: map_at_20 |
|
value: 0.6669999999999999 |
|
- type: map_at_3 |
|
value: 0.40299999999999997 |
|
- type: map_at_5 |
|
value: 0.47600000000000003 |
|
- type: mrr_at_1 |
|
value: 0.164 |
|
- type: mrr_at_10 |
|
value: 0.584 |
|
- type: mrr_at_100 |
|
value: 0.8240000000000001 |
|
- type: mrr_at_1000 |
|
value: 0.9769999999999999 |
|
- type: mrr_at_20 |
|
value: 0.6669999999999999 |
|
- type: mrr_at_3 |
|
value: 0.40299999999999997 |
|
- type: mrr_at_5 |
|
value: 0.47600000000000003 |
|
- type: ndcg_at_1 |
|
value: 0.164 |
|
- type: ndcg_at_10 |
|
value: 0.8670000000000001 |
|
- type: ndcg_at_100 |
|
value: 2.443 |
|
- type: ndcg_at_1000 |
|
value: 8.671 |
|
- type: ndcg_at_20 |
|
value: 1.176 |
|
- type: ndcg_at_3 |
|
value: 0.47800000000000004 |
|
- type: ndcg_at_5 |
|
value: 0.612 |
|
- type: precision_at_1 |
|
value: 0.164 |
|
- type: precision_at_10 |
|
value: 0.18 |
|
- type: precision_at_100 |
|
value: 0.10200000000000001 |
|
- type: precision_at_1000 |
|
value: 0.064 |
|
- type: precision_at_20 |
|
value: 0.152 |
|
- type: precision_at_3 |
|
value: 0.232 |
|
- type: precision_at_5 |
|
value: 0.20500000000000002 |
|
- type: recall_at_1 |
|
value: 0.164 |
|
- type: recall_at_10 |
|
value: 1.802 |
|
- type: recall_at_100 |
|
value: 10.156 |
|
- type: recall_at_1000 |
|
value: 64.21 |
|
- type: recall_at_20 |
|
value: 3.0300000000000002 |
|
- type: recall_at_3 |
|
value: 0.696 |
|
- type: recall_at_5 |
|
value: 1.024 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: GEM/opusparcus |
|
name: MTEB OpusparcusPC (fra-Latn) |
|
config: fra-Latn |
|
split: test |
|
revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 73.433242506812 |
|
- type: cos_sim_ap |
|
value: 86.03577758642086 |
|
- type: cos_sim_f1 |
|
value: 82.1602478972997 |
|
- type: cos_sim_precision |
|
value: 74.12140575079871 |
|
- type: cos_sim_recall |
|
value: 92.15491559086395 |
|
- type: dot_accuracy |
|
value: 68.8692098092643 |
|
- type: dot_ap |
|
value: 75.51070462676913 |
|
- type: dot_f1 |
|
value: 81.47547628698824 |
|
- type: dot_precision |
|
value: 68.83561643835617 |
|
- type: dot_recall |
|
value: 99.80139026812313 |
|
- type: euclidean_accuracy |
|
value: 73.84196185286103 |
|
- type: euclidean_ap |
|
value: 86.27910998502644 |
|
- type: euclidean_f1 |
|
value: 82.5531914893617 |
|
- type: euclidean_precision |
|
value: 72.22635889798957 |
|
- type: euclidean_recall |
|
value: 96.32571996027805 |
|
- type: manhattan_accuracy |
|
value: 73.9100817438692 |
|
- type: manhattan_ap |
|
value: 86.43527306280204 |
|
- type: manhattan_f1 |
|
value: 82.57349808265872 |
|
- type: manhattan_precision |
|
value: 72.31343283582089 |
|
- type: manhattan_recall |
|
value: 96.22641509433963 |
|
- type: max_accuracy |
|
value: 73.9100817438692 |
|
- type: max_ap |
|
value: 86.43527306280204 |
|
- type: max_f1 |
|
value: 82.57349808265872 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: paws-x |
|
name: MTEB PawsX (fra-Latn) |
|
config: fra-Latn |
|
split: test |
|
revision: 8a04d940a42cd40658986fdd8e3da561533a3646 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 61.550000000000004 |
|
- type: cos_sim_ap |
|
value: 60.30864957174996 |
|
- type: cos_sim_f1 |
|
value: 62.891311994372145 |
|
- type: cos_sim_precision |
|
value: 46.08247422680412 |
|
- type: cos_sim_recall |
|
value: 99.00332225913621 |
|
- type: dot_accuracy |
|
value: 55.35 |
|
- type: dot_ap |
|
value: 47.540176633815165 |
|
- type: dot_f1 |
|
value: 62.20227821884707 |
|
- type: dot_precision |
|
value: 45.18555667001003 |
|
- type: dot_recall |
|
value: 99.77851605758582 |
|
- type: euclidean_accuracy |
|
value: 61.95 |
|
- type: euclidean_ap |
|
value: 60.44070441806914 |
|
- type: euclidean_f1 |
|
value: 62.89978678038379 |
|
- type: euclidean_precision |
|
value: 46.31083202511774 |
|
- type: euclidean_recall |
|
value: 98.00664451827242 |
|
- type: manhattan_accuracy |
|
value: 61.9 |
|
- type: manhattan_ap |
|
value: 60.52939878134297 |
|
- type: manhattan_f1 |
|
value: 63.034188034188034 |
|
- type: manhattan_precision |
|
value: 46.45669291338583 |
|
- type: manhattan_recall |
|
value: 98.00664451827242 |
|
- type: max_accuracy |
|
value: 61.95 |
|
- type: max_ap |
|
value: 60.52939878134297 |
|
- type: max_f1 |
|
value: 63.034188034188034 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: Lajavaness/SICK-fr |
|
name: MTEB SICKFr (fra-Latn) |
|
config: fra-Latn |
|
split: test |
|
revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 55.697943925847646 |
|
- type: cos_sim_spearman |
|
value: 53.33151992866752 |
|
- type: euclidean_pearson |
|
value: 54.32882764397367 |
|
- type: euclidean_spearman |
|
value: 53.54968438609837 |
|
- type: manhattan_pearson |
|
value: 54.56634524641888 |
|
- type: manhattan_spearman |
|
value: 53.81344727168701 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (fra-Latn) |
|
config: fra-Latn |
|
split: test |
|
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 22.771197036286605 |
|
- type: cos_sim_spearman |
|
value: 60.29016180301653 |
|
- type: euclidean_pearson |
|
value: 35.31319988418939 |
|
- type: euclidean_spearman |
|
value: 59.61398871828641 |
|
- type: manhattan_pearson |
|
value: 36.10315029818106 |
|
- type: manhattan_spearman |
|
value: 60.5122301133988 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsb_multi_mt |
|
name: MTEB STSBenchmarkMultilingualSTS (fra-Latn) |
|
config: fra-Latn |
|
split: test |
|
revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 47.730796921644384 |
|
- type: cos_sim_spearman |
|
value: 49.54059034135741 |
|
- type: euclidean_pearson |
|
value: 49.48474815018905 |
|
- type: euclidean_spearman |
|
value: 50.71533884079761 |
|
- type: manhattan_pearson |
|
value: 50.10488858533032 |
|
- type: manhattan_spearman |
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value: 51.1375710610132 |
|
- task: |
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type: Summarization |
|
dataset: |
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type: lyon-nlp/summarization-summeval-fr-p2p |
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name: MTEB SummEvalFr (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: b385812de6a9577b6f4d0f88c6a6e35395a94054 |
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metrics: |
|
- type: cos_sim_pearson |
|
value: 29.102661066592816 |
|
- type: cos_sim_spearman |
|
value: 29.615000554218955 |
|
- type: dot_pearson |
|
value: 19.77690299595119 |
|
- type: dot_spearman |
|
value: 19.112834848310158 |
|
- task: |
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type: Reranking |
|
dataset: |
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type: lyon-nlp/mteb-fr-reranking-syntec-s2p |
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name: MTEB SyntecReranking (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: daf0863838cd9e3ba50544cdce3ac2b338a1b0ad |
|
metrics: |
|
- type: map |
|
value: 37.372655122655125 |
|
- type: mrr |
|
value: 37.28174603174604 |
|
- task: |
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type: Retrieval |
|
dataset: |
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type: lyon-nlp/mteb-fr-retrieval-syntec-s2p |
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name: MTEB SyntecRetrieval (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: 19661ccdca4dfc2d15122d776b61685f48c68ca9 |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.0 |
|
- type: map_at_10 |
|
value: 6.816999999999999 |
|
- type: map_at_100 |
|
value: 9.522 |
|
- type: map_at_1000 |
|
value: 9.522 |
|
- type: map_at_20 |
|
value: 8.402 |
|
- type: map_at_3 |
|
value: 4.167 |
|
- type: map_at_5 |
|
value: 4.867 |
|
- type: mrr_at_1 |
|
value: 2.0 |
|
- type: mrr_at_10 |
|
value: 6.816999999999999 |
|
- type: mrr_at_100 |
|
value: 9.522 |
|
- type: mrr_at_1000 |
|
value: 9.522 |
|
- type: mrr_at_20 |
|
value: 8.402 |
|
- type: mrr_at_3 |
|
value: 4.167 |
|
- type: mrr_at_5 |
|
value: 4.867 |
|
- type: ndcg_at_1 |
|
value: 2.0 |
|
- type: ndcg_at_10 |
|
value: 10.940999999999999 |
|
- type: ndcg_at_100 |
|
value: 25.96 |
|
- type: ndcg_at_1000 |
|
value: 25.96 |
|
- type: ndcg_at_20 |
|
value: 16.742 |
|
- type: ndcg_at_3 |
|
value: 4.893 |
|
- type: ndcg_at_5 |
|
value: 6.141 |
|
- type: precision_at_1 |
|
value: 2.0 |
|
- type: precision_at_10 |
|
value: 2.5 |
|
- type: precision_at_100 |
|
value: 1.0 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_20 |
|
value: 2.4 |
|
- type: precision_at_3 |
|
value: 2.333 |
|
- type: precision_at_5 |
|
value: 2.0 |
|
- type: recall_at_1 |
|
value: 2.0 |
|
- type: recall_at_10 |
|
value: 25.0 |
|
- type: recall_at_100 |
|
value: 100.0 |
|
- type: recall_at_1000 |
|
value: 100.0 |
|
- type: recall_at_20 |
|
value: 48.0 |
|
- type: recall_at_3 |
|
value: 7.000000000000001 |
|
- type: recall_at_5 |
|
value: 10.0 |
|
- task: |
|
type: Retrieval |
|
dataset: |
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type: jinaai/xpqa |
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name: MTEB XPQARetrieval (fra-Latn) |
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config: fra-Latn |
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split: test |
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revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.437 |
|
- type: map_at_10 |
|
value: 13.574 |
|
- type: map_at_100 |
|
value: 14.265 |
|
- type: map_at_1000 |
|
value: 14.527999999999999 |
|
- type: map_at_20 |
|
value: 13.834 |
|
- type: map_at_3 |
|
value: 12.277000000000001 |
|
- type: map_at_5 |
|
value: 12.936 |
|
- type: mrr_at_1 |
|
value: 14.285999999999998 |
|
- type: mrr_at_10 |
|
value: 18.269 |
|
- type: mrr_at_100 |
|
value: 18.991 |
|
- type: mrr_at_1000 |
|
value: 19.15 |
|
- type: mrr_at_20 |
|
value: 18.598 |
|
- type: mrr_at_3 |
|
value: 17.0 |
|
- type: mrr_at_5 |
|
value: 17.681 |
|
- type: ndcg_at_1 |
|
value: 14.285999999999998 |
|
- type: ndcg_at_10 |
|
value: 16.447 |
|
- type: ndcg_at_100 |
|
value: 20.617 |
|
- type: ndcg_at_1000 |
|
value: 27.589000000000002 |
|
- type: ndcg_at_20 |
|
value: 17.455000000000002 |
|
- type: ndcg_at_3 |
|
value: 14.540000000000001 |
|
- type: ndcg_at_5 |
|
value: 15.084 |
|
- type: precision_at_1 |
|
value: 14.285999999999998 |
|
- type: precision_at_10 |
|
value: 3.698 |
|
- type: precision_at_100 |
|
value: 0.734 |
|
- type: precision_at_1000 |
|
value: 0.18 |
|
- type: precision_at_20 |
|
value: 2.163 |
|
- type: precision_at_3 |
|
value: 8.366999999999999 |
|
- type: precision_at_5 |
|
value: 5.928 |
|
- type: recall_at_1 |
|
value: 9.437 |
|
- type: recall_at_10 |
|
value: 20.16 |
|
- type: recall_at_100 |
|
value: 38.527 |
|
- type: recall_at_1000 |
|
value: 85.102 |
|
- type: recall_at_20 |
|
value: 23.632 |
|
- type: recall_at_3 |
|
value: 14.562 |
|
- type: recall_at_5 |
|
value: 16.8 |
|
|
|
language: |
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- fr |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
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|
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# llm2vec-croissant-mntp |
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|
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This model is a fine-tuned version of [croissantllm/CroissantCool-v0.2](https://huggingface.co/croissantllm/CroissantCool-v0.2) on [asi/wikitext_fr](asi/wikitext_fr). |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8867 |
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- Accuracy: 0.6078 |
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|
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## Model description |
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|
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More information needed |
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|
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## Intended uses & limitations |
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|
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More information needed |
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|
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## Training and evaluation data |
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|
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More information needed |
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|
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## Training procedure |
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|
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### Training hyperparameters |
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|
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3.0 |
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|
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### Training results |
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|
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| No log | 0.0884 | 100 | 4.7866 | 0.1990 | |
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| No log | 0.1768 | 200 | 4.0496 | 0.3309 | |
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| No log | 0.2653 | 300 | 3.6525 | 0.3779 | |
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| No log | 0.3537 | 400 | 3.2410 | 0.4258 | |
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| 3.9116 | 0.4421 | 500 | 3.6305 | 0.3912 | |
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| 3.9116 | 0.5305 | 600 | 3.1770 | 0.4406 | |
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| 3.9116 | 0.6189 | 700 | 2.4478 | 0.5199 | |
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| 3.9116 | 0.7073 | 800 | 2.2383 | 0.5508 | |
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| 3.9116 | 0.7958 | 900 | 2.1547 | 0.5635 | |
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| 2.4568 | 0.8842 | 1000 | 2.0868 | 0.5759 | |
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| 2.4568 | 0.9726 | 1100 | 2.0399 | 0.5820 | |
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| 2.4568 | 1.0610 | 1200 | 2.0102 | 0.5873 | |
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| 2.4568 | 1.1494 | 1300 | 1.9805 | 0.5897 | |
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| 2.4568 | 1.2378 | 1400 | 1.9590 | 0.5955 | |
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| 1.9305 | 1.3263 | 1500 | 1.9381 | 0.5982 | |
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| 1.9305 | 1.4147 | 1600 | 1.9249 | 0.5995 | |
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| 1.9305 | 1.5031 | 1700 | 1.9223 | 0.6017 | |
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| 1.9305 | 1.5915 | 1800 | 1.9091 | 0.6037 | |
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| 1.9305 | 1.6799 | 1900 | 1.9038 | 0.6042 | |
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| 1.8511 | 1.7683 | 2000 | 1.8982 | 0.6045 | |
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| 1.8511 | 1.8568 | 2100 | 1.8924 | 0.6060 | |
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| 1.8511 | 1.9452 | 2200 | 1.8844 | 0.6072 | |
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| 1.8511 | 2.0336 | 2300 | 1.8873 | 0.6087 | |
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| 1.8511 | 2.1220 | 2400 | 1.8889 | 0.6068 | |
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| 1.8197 | 2.2104 | 2500 | 1.8848 | 0.6080 | |
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| 1.8197 | 2.2989 | 2600 | 1.8736 | 0.6091 | |
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| 1.8197 | 2.3873 | 2700 | 1.8858 | 0.6072 | |
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| 1.8197 | 2.4757 | 2800 | 1.8814 | 0.6088 | |
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| 1.8197 | 2.5641 | 2900 | 1.8649 | 0.6103 | |
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| 1.8116 | 2.6525 | 3000 | 1.8647 | 0.6091 | |
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| 1.8116 | 2.7409 | 3100 | 1.8755 | 0.6101 | |
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| 1.8116 | 2.8294 | 3200 | 1.8755 | 0.6099 | |
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| 1.8116 | 2.9178 | 3300 | 1.8867 | 0.6078 | |
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|
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### Framework versions |
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|
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- Transformers 4.40.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
