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--- |
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tags: |
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- sentence-transformers |
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- sentence-similarity |
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- feature-extraction |
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- generated_from_trainer |
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- dataset_size:86648 |
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- loss:MSELoss |
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widget: |
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- source_sentence: Familienberaterin |
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sentences: |
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- electric power station operator |
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- venue booker & promoter |
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- betrieblicher Aus- und Weiterbildner/betriebliche Aus- und Weiterbildnerin |
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- source_sentence: high school RS teacher |
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sentences: |
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- infantryman |
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- Schnellbedienungsrestaurantteamleiter |
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- drill setup operator |
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- source_sentence: lighting designer |
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sentences: |
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- software support manager |
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- 直升机维护协调员 |
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- bus maintenance supervisor |
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- source_sentence: 机场消防员 |
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sentences: |
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- Flake操作员 |
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- técnico en gestión de residuos peligrosos/técnica en gestión de residuos peligrosos |
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- 专门学校老师 |
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- source_sentence: Entwicklerin für mobile Anwendungen |
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sentences: |
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- fashion design expert |
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- Mergers-and-Acquisitions-Analyst/Mergers-and-Acquisitions-Analystin |
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- commercial bid manager |
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pipeline_tag: sentence-similarity |
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library_name: sentence-transformers |
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metrics: |
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- cosine_accuracy@1 |
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- cosine_accuracy@20 |
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- cosine_accuracy@50 |
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- cosine_accuracy@100 |
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- cosine_accuracy@150 |
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- cosine_accuracy@200 |
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- cosine_precision@1 |
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- cosine_precision@20 |
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- cosine_precision@50 |
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- cosine_precision@100 |
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- cosine_precision@150 |
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- cosine_precision@200 |
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- cosine_recall@1 |
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- cosine_recall@20 |
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- cosine_recall@50 |
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- cosine_recall@100 |
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- cosine_recall@150 |
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- cosine_recall@200 |
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- cosine_ndcg@1 |
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- cosine_ndcg@20 |
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- cosine_ndcg@50 |
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- cosine_ndcg@100 |
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- cosine_ndcg@150 |
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- cosine_ndcg@200 |
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- cosine_mrr@1 |
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- cosine_mrr@20 |
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- cosine_mrr@50 |
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- cosine_mrr@100 |
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- cosine_mrr@150 |
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- cosine_mrr@200 |
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- cosine_map@1 |
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- cosine_map@20 |
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- cosine_map@50 |
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- cosine_map@100 |
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- cosine_map@150 |
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- cosine_map@200 |
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- cosine_map@500 |
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model-index: |
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- name: SentenceTransformer |
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results: |
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- task: |
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type: information-retrieval |
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name: Information Retrieval |
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dataset: |
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name: full en |
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type: full_en |
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metrics: |
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- type: cosine_accuracy@1 |
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value: 0.6285714285714286 |
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name: Cosine Accuracy@1 |
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- type: cosine_accuracy@20 |
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value: 0.9714285714285714 |
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name: Cosine Accuracy@20 |
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- type: cosine_accuracy@50 |
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value: 0.9904761904761905 |
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name: Cosine Accuracy@50 |
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- type: cosine_accuracy@100 |
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value: 0.9904761904761905 |
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name: Cosine Accuracy@100 |
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|
- type: cosine_accuracy@150 |
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value: 0.9904761904761905 |
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name: Cosine Accuracy@150 |
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- type: cosine_accuracy@200 |
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value: 0.9904761904761905 |
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name: Cosine Accuracy@200 |
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- type: cosine_precision@1 |
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value: 0.6285714285714286 |
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name: Cosine Precision@1 |
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- type: cosine_precision@20 |
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value: 0.4723809523809524 |
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name: Cosine Precision@20 |
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- type: cosine_precision@50 |
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value: 0.2838095238095238 |
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name: Cosine Precision@50 |
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- type: cosine_precision@100 |
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value: 0.1706666666666667 |
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name: Cosine Precision@100 |
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- type: cosine_precision@150 |
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value: 0.12285714285714286 |
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name: Cosine Precision@150 |
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- type: cosine_precision@200 |
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value: 0.09700000000000002 |
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name: Cosine Precision@200 |
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- type: cosine_recall@1 |
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value: 0.06568451704213447 |
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name: Cosine Recall@1 |
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- type: cosine_recall@20 |
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value: 0.5041312032991911 |
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name: Cosine Recall@20 |
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- type: cosine_recall@50 |
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value: 0.6762963371727007 |
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name: Cosine Recall@50 |
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- type: cosine_recall@100 |
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value: 0.7798036464336738 |
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name: Cosine Recall@100 |
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- type: cosine_recall@150 |
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value: 0.8311908383371492 |
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name: Cosine Recall@150 |
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- type: cosine_recall@200 |
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value: 0.8655400214018215 |
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name: Cosine Recall@200 |
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- type: cosine_ndcg@1 |
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value: 0.6285714285714286 |
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|
name: Cosine Ndcg@1 |
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- type: cosine_ndcg@20 |
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value: 0.6385286667884668 |
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name: Cosine Ndcg@20 |
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- type: cosine_ndcg@50 |
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value: 0.6505087993598385 |
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name: Cosine Ndcg@50 |
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- type: cosine_ndcg@100 |
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value: 0.7009585791000247 |
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name: Cosine Ndcg@100 |
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- type: cosine_ndcg@150 |
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value: 0.7228549618650749 |
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name: Cosine Ndcg@150 |
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- type: cosine_ndcg@200 |
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value: 0.7370730818153396 |
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name: Cosine Ndcg@200 |
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- type: cosine_mrr@1 |
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value: 0.6285714285714286 |
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name: Cosine Mrr@1 |
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- type: cosine_mrr@20 |
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value: 0.7790726817042607 |
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name: Cosine Mrr@20 |
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- type: cosine_mrr@50 |
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value: 0.7797979143260452 |
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name: Cosine Mrr@50 |
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- type: cosine_mrr@100 |
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value: 0.7797979143260452 |
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name: Cosine Mrr@100 |
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|
- type: cosine_mrr@150 |
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value: 0.7797979143260452 |
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name: Cosine Mrr@150 |
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- type: cosine_mrr@200 |
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value: 0.7797979143260452 |
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name: Cosine Mrr@200 |
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- type: cosine_map@1 |
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value: 0.6285714285714286 |
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|
name: Cosine Map@1 |
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- type: cosine_map@20 |
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value: 0.4949002324392317 |
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name: Cosine Map@20 |
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- type: cosine_map@50 |
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|
value: 0.47542864021103454 |
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name: Cosine Map@50 |
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|
- type: cosine_map@100 |
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|
value: 0.5027685735699932 |
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name: Cosine Map@100 |
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|
- type: cosine_map@150 |
|
|
value: 0.5108956115342047 |
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|
name: Cosine Map@150 |
|
|
- type: cosine_map@200 |
|
|
value: 0.5152152246235047 |
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|
name: Cosine Map@200 |
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- type: cosine_map@500 |
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|
value: 0.5211733943510876 |
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|
name: Cosine Map@500 |
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- task: |
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type: information-retrieval |
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name: Information Retrieval |
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dataset: |
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name: full es |
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type: full_es |
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metrics: |
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- type: cosine_accuracy@1 |
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value: 0.11351351351351352 |
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name: Cosine Accuracy@1 |
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- type: cosine_accuracy@20 |
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value: 1.0 |
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name: Cosine Accuracy@20 |
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- type: cosine_accuracy@50 |
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value: 1.0 |
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name: Cosine Accuracy@50 |
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- type: cosine_accuracy@100 |
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value: 1.0 |
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name: Cosine Accuracy@100 |
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- type: cosine_accuracy@150 |
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value: 1.0 |
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name: Cosine Accuracy@150 |
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- type: cosine_accuracy@200 |
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value: 1.0 |
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name: Cosine Accuracy@200 |
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- type: cosine_precision@1 |
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value: 0.11351351351351352 |
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name: Cosine Precision@1 |
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- type: cosine_precision@20 |
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value: 0.5213513513513512 |
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name: Cosine Precision@20 |
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- type: cosine_precision@50 |
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value: 0.33891891891891895 |
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name: Cosine Precision@50 |
|
|
- type: cosine_precision@100 |
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value: 0.2141081081081081 |
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name: Cosine Precision@100 |
|
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- type: cosine_precision@150 |
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value: 0.16104504504504505 |
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name: Cosine Precision@150 |
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- type: cosine_precision@200 |
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value: 0.13094594594594594 |
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name: Cosine Precision@200 |
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- type: cosine_recall@1 |
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value: 0.0035045234969014166 |
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name: Cosine Recall@1 |
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- type: cosine_recall@20 |
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value: 0.34830621955762764 |
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name: Cosine Recall@20 |
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- type: cosine_recall@50 |
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value: 0.5043797869988105 |
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|
name: Cosine Recall@50 |
|
|
- type: cosine_recall@100 |
|
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value: 0.5962566893615484 |
|
|
name: Cosine Recall@100 |
|
|
- type: cosine_recall@150 |
|
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value: 0.6539916045900668 |
|
|
name: Cosine Recall@150 |
|
|
- type: cosine_recall@200 |
|
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value: 0.7027707655811134 |
|
|
name: Cosine Recall@200 |
|
|
- type: cosine_ndcg@1 |
|
|
value: 0.11351351351351352 |
|
|
name: Cosine Ndcg@1 |
|
|
- type: cosine_ndcg@20 |
|
|
value: 0.5638160555705326 |
|
|
name: Cosine Ndcg@20 |
|
|
- type: cosine_ndcg@50 |
|
|
value: 0.5286289587475489 |
|
|
name: Cosine Ndcg@50 |
|
|
- type: cosine_ndcg@100 |
|
|
value: 0.5494533442820461 |
|
|
name: Cosine Ndcg@100 |
|
|
- type: cosine_ndcg@150 |
|
|
value: 0.5778904564772578 |
|
|
name: Cosine Ndcg@150 |
|
|
- type: cosine_ndcg@200 |
|
|
value: 0.6002374248801999 |
|
|
name: Cosine Ndcg@200 |
|
|
- type: cosine_mrr@1 |
|
|
value: 0.11351351351351352 |
|
|
name: Cosine Mrr@1 |
|
|
- type: cosine_mrr@20 |
|
|
value: 0.55 |
|
|
name: Cosine Mrr@20 |
|
|
- type: cosine_mrr@50 |
|
|
value: 0.55 |
|
|
name: Cosine Mrr@50 |
|
|
- type: cosine_mrr@100 |
|
|
value: 0.55 |
|
|
name: Cosine Mrr@100 |
|
|
- type: cosine_mrr@150 |
|
|
value: 0.55 |
|
|
name: Cosine Mrr@150 |
|
|
- type: cosine_mrr@200 |
|
|
value: 0.55 |
|
|
name: Cosine Mrr@200 |
|
|
- type: cosine_map@1 |
|
|
value: 0.11351351351351352 |
|
|
name: Cosine Map@1 |
|
|
- type: cosine_map@20 |
|
|
value: 0.4321212731877681 |
|
|
name: Cosine Map@20 |
|
|
- type: cosine_map@50 |
|
|
value: 0.3662438776904182 |
|
|
name: Cosine Map@50 |
|
|
- type: cosine_map@100 |
|
|
value: 0.3676467044477579 |
|
|
name: Cosine Map@100 |
|
|
- type: cosine_map@150 |
|
|
value: 0.37914071893635704 |
|
|
name: Cosine Map@150 |
|
|
- type: cosine_map@200 |
|
|
value: 0.3864291047810966 |
|
|
name: Cosine Map@200 |
|
|
- type: cosine_map@500 |
|
|
value: 0.3967448814407886 |
|
|
name: Cosine Map@500 |
|
|
- task: |
|
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type: information-retrieval |
|
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name: Information Retrieval |
|
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dataset: |
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name: full de |
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type: full_de |
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metrics: |
|
|
- type: cosine_accuracy@1 |
|
|
value: 0.2955665024630542 |
|
|
name: Cosine Accuracy@1 |
|
|
- type: cosine_accuracy@20 |
|
|
value: 0.9605911330049262 |
|
|
name: Cosine Accuracy@20 |
|
|
- type: cosine_accuracy@50 |
|
|
value: 0.9802955665024631 |
|
|
name: Cosine Accuracy@50 |
|
|
- type: cosine_accuracy@100 |
|
|
value: 0.9852216748768473 |
|
|
name: Cosine Accuracy@100 |
|
|
- type: cosine_accuracy@150 |
|
|
value: 0.9852216748768473 |
|
|
name: Cosine Accuracy@150 |
|
|
- type: cosine_accuracy@200 |
|
|
value: 0.9901477832512315 |
|
|
name: Cosine Accuracy@200 |
|
|
- type: cosine_precision@1 |
|
|
value: 0.2955665024630542 |
|
|
name: Cosine Precision@1 |
|
|
- type: cosine_precision@20 |
|
|
value: 0.424384236453202 |
|
|
name: Cosine Precision@20 |
|
|
- type: cosine_precision@50 |
|
|
value: 0.29064039408866993 |
|
|
name: Cosine Precision@50 |
|
|
- type: cosine_precision@100 |
|
|
value: 0.19019704433497536 |
|
|
name: Cosine Precision@100 |
|
|
- type: cosine_precision@150 |
|
|
value: 0.14476190476190476 |
|
|
name: Cosine Precision@150 |
|
|
- type: cosine_precision@200 |
|
|
value: 0.1177832512315271 |
|
|
name: Cosine Precision@200 |
|
|
- type: cosine_recall@1 |
|
|
value: 0.01108543831680986 |
|
|
name: Cosine Recall@1 |
|
|
- type: cosine_recall@20 |
|
|
value: 0.2623989771425487 |
|
|
name: Cosine Recall@20 |
|
|
- type: cosine_recall@50 |
|
|
value: 0.399936827395569 |
|
|
name: Cosine Recall@50 |
|
|
- type: cosine_recall@100 |
|
|
value: 0.5011599542158983 |
|
|
name: Cosine Recall@100 |
|
|
- type: cosine_recall@150 |
|
|
value: 0.5599024076006294 |
|
|
name: Cosine Recall@150 |
|
|
- type: cosine_recall@200 |
|
|
value: 0.6019565140878311 |
|
|
name: Cosine Recall@200 |
|
|
- type: cosine_ndcg@1 |
|
|
value: 0.2955665024630542 |
|
|
name: Cosine Ndcg@1 |
|
|
- type: cosine_ndcg@20 |
|
|
value: 0.46461290935992494 |
|
|
name: Cosine Ndcg@20 |
|
|
- type: cosine_ndcg@50 |
|
|
value: 0.43636700085765784 |
|
|
name: Cosine Ndcg@50 |
|
|
- type: cosine_ndcg@100 |
|
|
value: 0.4594232150790335 |
|
|
name: Cosine Ndcg@100 |
|
|
- type: cosine_ndcg@150 |
|
|
value: 0.4887319216460325 |
|
|
name: Cosine Ndcg@150 |
|
|
- type: cosine_ndcg@200 |
|
|
value: 0.5085159310260775 |
|
|
name: Cosine Ndcg@200 |
|
|
- type: cosine_mrr@1 |
|
|
value: 0.2955665024630542 |
|
|
name: Cosine Mrr@1 |
|
|
- type: cosine_mrr@20 |
|
|
value: 0.503435229891329 |
|
|
name: Cosine Mrr@20 |
|
|
- type: cosine_mrr@50 |
|
|
value: 0.5041035247761447 |
|
|
name: Cosine Mrr@50 |
|
|
- type: cosine_mrr@100 |
|
|
value: 0.5041884576791513 |
|
|
name: Cosine Mrr@100 |
|
|
- type: cosine_mrr@150 |
|
|
value: 0.5041884576791513 |
|
|
name: Cosine Mrr@150 |
|
|
- type: cosine_mrr@200 |
|
|
value: 0.5042166068698621 |
|
|
name: Cosine Mrr@200 |
|
|
- type: cosine_map@1 |
|
|
value: 0.2955665024630542 |
|
|
name: Cosine Map@1 |
|
|
- type: cosine_map@20 |
|
|
value: 0.3326012942578798 |
|
|
name: Cosine Map@20 |
|
|
- type: cosine_map@50 |
|
|
value: 0.2779781159809199 |
|
|
name: Cosine Map@50 |
|
|
- type: cosine_map@100 |
|
|
value: 0.27530357902528746 |
|
|
name: Cosine Map@100 |
|
|
- type: cosine_map@150 |
|
|
value: 0.2859029789549631 |
|
|
name: Cosine Map@150 |
|
|
- type: cosine_map@200 |
|
|
value: 0.29192358526577794 |
|
|
name: Cosine Map@200 |
|
|
- type: cosine_map@500 |
|
|
value: 0.3037728006457777 |
|
|
name: Cosine Map@500 |
|
|
- task: |
|
|
type: information-retrieval |
|
|
name: Information Retrieval |
|
|
dataset: |
|
|
name: full zh |
|
|
type: full_zh |
|
|
metrics: |
|
|
- type: cosine_accuracy@1 |
|
|
value: 0.6504854368932039 |
|
|
name: Cosine Accuracy@1 |
|
|
- type: cosine_accuracy@20 |
|
|
value: 0.970873786407767 |
|
|
name: Cosine Accuracy@20 |
|
|
- type: cosine_accuracy@50 |
|
|
value: 0.9805825242718447 |
|
|
name: Cosine Accuracy@50 |
|
|
- type: cosine_accuracy@100 |
|
|
value: 0.9902912621359223 |
|
|
name: Cosine Accuracy@100 |
|
|
- type: cosine_accuracy@150 |
|
|
value: 0.9902912621359223 |
|
|
name: Cosine Accuracy@150 |
|
|
- type: cosine_accuracy@200 |
|
|
value: 0.9902912621359223 |
|
|
name: Cosine Accuracy@200 |
|
|
- type: cosine_precision@1 |
|
|
value: 0.6504854368932039 |
|
|
name: Cosine Precision@1 |
|
|
- type: cosine_precision@20 |
|
|
value: 0.4461165048543689 |
|
|
name: Cosine Precision@20 |
|
|
- type: cosine_precision@50 |
|
|
value: 0.26932038834951455 |
|
|
name: Cosine Precision@50 |
|
|
- type: cosine_precision@100 |
|
|
value: 0.16601941747572818 |
|
|
name: Cosine Precision@100 |
|
|
- type: cosine_precision@150 |
|
|
value: 0.12000000000000002 |
|
|
name: Cosine Precision@150 |
|
|
- type: cosine_precision@200 |
|
|
value: 0.09475728155339808 |
|
|
name: Cosine Precision@200 |
|
|
- type: cosine_recall@1 |
|
|
value: 0.06125809321810901 |
|
|
name: Cosine Recall@1 |
|
|
- type: cosine_recall@20 |
|
|
value: 0.4798173076061309 |
|
|
name: Cosine Recall@20 |
|
|
- type: cosine_recall@50 |
|
|
value: 0.6511259115267456 |
|
|
name: Cosine Recall@50 |
|
|
- type: cosine_recall@100 |
|
|
value: 0.7667280032499174 |
|
|
name: Cosine Recall@100 |
|
|
- type: cosine_recall@150 |
|
|
value: 0.8234348132226993 |
|
|
name: Cosine Recall@150 |
|
|
- type: cosine_recall@200 |
|
|
value: 0.8570886860782638 |
|
|
name: Cosine Recall@200 |
|
|
- type: cosine_ndcg@1 |
|
|
value: 0.6504854368932039 |
|
|
name: Cosine Ndcg@1 |
|
|
- type: cosine_ndcg@20 |
|
|
value: 0.6163434250133266 |
|
|
name: Cosine Ndcg@20 |
|
|
- type: cosine_ndcg@50 |
|
|
value: 0.6306194061713684 |
|
|
name: Cosine Ndcg@50 |
|
|
- type: cosine_ndcg@100 |
|
|
value: 0.6852740031621496 |
|
|
name: Cosine Ndcg@100 |
|
|
- type: cosine_ndcg@150 |
|
|
value: 0.7087858531025408 |
|
|
name: Cosine Ndcg@150 |
|
|
- type: cosine_ndcg@200 |
|
|
value: 0.7227726687256436 |
|
|
name: Cosine Ndcg@200 |
|
|
- type: cosine_mrr@1 |
|
|
value: 0.6504854368932039 |
|
|
name: Cosine Mrr@1 |
|
|
- type: cosine_mrr@20 |
|
|
value: 0.7938511326860843 |
|
|
name: Cosine Mrr@20 |
|
|
- type: cosine_mrr@50 |
|
|
value: 0.7941135310067349 |
|
|
name: Cosine Mrr@50 |
|
|
- type: cosine_mrr@100 |
|
|
value: 0.7943002375041209 |
|
|
name: Cosine Mrr@100 |
|
|
- type: cosine_mrr@150 |
|
|
value: 0.7943002375041209 |
|
|
name: Cosine Mrr@150 |
|
|
- type: cosine_mrr@200 |
|
|
value: 0.7943002375041209 |
|
|
name: Cosine Mrr@200 |
|
|
- type: cosine_map@1 |
|
|
value: 0.6504854368932039 |
|
|
name: Cosine Map@1 |
|
|
- type: cosine_map@20 |
|
|
value: 0.4673451367444491 |
|
|
name: Cosine Map@20 |
|
|
- type: cosine_map@50 |
|
|
value: 0.4491601687897158 |
|
|
name: Cosine Map@50 |
|
|
- type: cosine_map@100 |
|
|
value: 0.4759775327060125 |
|
|
name: Cosine Map@100 |
|
|
- type: cosine_map@150 |
|
|
value: 0.484283864447002 |
|
|
name: Cosine Map@150 |
|
|
- type: cosine_map@200 |
|
|
value: 0.4885403171787604 |
|
|
name: Cosine Map@200 |
|
|
- type: cosine_map@500 |
|
|
value: 0.4948931148880558 |
|
|
name: Cosine Map@500 |
|
|
- task: |
|
|
type: information-retrieval |
|
|
name: Information Retrieval |
|
|
dataset: |
|
|
name: mix es |
|
|
type: mix_es |
|
|
metrics: |
|
|
- type: cosine_accuracy@1 |
|
|
value: 0.6172646905876235 |
|
|
name: Cosine Accuracy@1 |
|
|
- type: cosine_accuracy@20 |
|
|
value: 0.9032761310452418 |
|
|
name: Cosine Accuracy@20 |
|
|
- type: cosine_accuracy@50 |
|
|
value: 0.9443577743109725 |
|
|
name: Cosine Accuracy@50 |
|
|
- type: cosine_accuracy@100 |
|
|
value: 0.9703588143525741 |
|
|
name: Cosine Accuracy@100 |
|
|
- type: cosine_accuracy@150 |
|
|
value: 0.9812792511700468 |
|
|
name: Cosine Accuracy@150 |
|
|
- type: cosine_accuracy@200 |
|
|
value: 0.9859594383775351 |
|
|
name: Cosine Accuracy@200 |
|
|
- type: cosine_precision@1 |
|
|
value: 0.6172646905876235 |
|
|
name: Cosine Precision@1 |
|
|
- type: cosine_precision@20 |
|
|
value: 0.10972438897555903 |
|
|
name: Cosine Precision@20 |
|
|
- type: cosine_precision@50 |
|
|
value: 0.04786271450858035 |
|
|
name: Cosine Precision@50 |
|
|
- type: cosine_precision@100 |
|
|
value: 0.025169006760270413 |
|
|
name: Cosine Precision@100 |
|
|
- type: cosine_precision@150 |
|
|
value: 0.017157219622118216 |
|
|
name: Cosine Precision@150 |
|
|
- type: cosine_precision@200 |
|
|
value: 0.013018720748829957 |
|
|
name: Cosine Precision@200 |
|
|
- type: cosine_recall@1 |
|
|
value: 0.2379838050664884 |
|
|
name: Cosine Recall@1 |
|
|
- type: cosine_recall@20 |
|
|
value: 0.8149369784315182 |
|
|
name: Cosine Recall@20 |
|
|
- type: cosine_recall@50 |
|
|
value: 0.8866788004853527 |
|
|
name: Cosine Recall@50 |
|
|
- type: cosine_recall@100 |
|
|
value: 0.9331773270930838 |
|
|
name: Cosine Recall@100 |
|
|
- type: cosine_recall@150 |
|
|
value: 0.9536141445657828 |
|
|
name: Cosine Recall@150 |
|
|
- type: cosine_recall@200 |
|
|
value: 0.9651759403709481 |
|
|
name: Cosine Recall@200 |
|
|
- type: cosine_ndcg@1 |
|
|
value: 0.6172646905876235 |
|
|
name: Cosine Ndcg@1 |
|
|
- type: cosine_ndcg@20 |
|
|
value: 0.6863945449619185 |
|
|
name: Cosine Ndcg@20 |
|
|
- type: cosine_ndcg@50 |
|
|
value: 0.7059805315894592 |
|
|
name: Cosine Ndcg@50 |
|
|
- type: cosine_ndcg@100 |
|
|
value: 0.7161349937562115 |
|
|
name: Cosine Ndcg@100 |
|
|
- type: cosine_ndcg@150 |
|
|
value: 0.7201494083175249 |
|
|
name: Cosine Ndcg@150 |
|
|
- type: cosine_ndcg@200 |
|
|
value: 0.722225937142632 |
|
|
name: Cosine Ndcg@200 |
|
|
- type: cosine_mrr@1 |
|
|
value: 0.6172646905876235 |
|
|
name: Cosine Mrr@1 |
|
|
- type: cosine_mrr@20 |
|
|
value: 0.6921361840847764 |
|
|
name: Cosine Mrr@20 |
|
|
- type: cosine_mrr@50 |
|
|
value: 0.6935275501084183 |
|
|
name: Cosine Mrr@50 |
|
|
- type: cosine_mrr@100 |
|
|
value: 0.6938924919697613 |
|
|
name: Cosine Mrr@100 |
|
|
- type: cosine_mrr@150 |
|
|
value: 0.6939819360030616 |
|
|
name: Cosine Mrr@150 |
|
|
- type: cosine_mrr@200 |
|
|
value: 0.6940082129440573 |
|
|
name: Cosine Mrr@200 |
|
|
- type: cosine_map@1 |
|
|
value: 0.6172646905876235 |
|
|
name: Cosine Map@1 |
|
|
- type: cosine_map@20 |
|
|
value: 0.6028333286973904 |
|
|
name: Cosine Map@20 |
|
|
- type: cosine_map@50 |
|
|
value: 0.6079882517976847 |
|
|
name: Cosine Map@50 |
|
|
- type: cosine_map@100 |
|
|
value: 0.6094136625128228 |
|
|
name: Cosine Map@100 |
|
|
- type: cosine_map@150 |
|
|
value: 0.6097807307495342 |
|
|
name: Cosine Map@150 |
|
|
- type: cosine_map@200 |
|
|
value: 0.6099278426294548 |
|
|
name: Cosine Map@200 |
|
|
- type: cosine_map@500 |
|
|
value: 0.6101218939355526 |
|
|
name: Cosine Map@500 |
|
|
- task: |
|
|
type: information-retrieval |
|
|
name: Information Retrieval |
|
|
dataset: |
|
|
name: mix de |
|
|
type: mix_de |
|
|
metrics: |
|
|
- type: cosine_accuracy@1 |
|
|
value: 0.5429017160686428 |
|
|
name: Cosine Accuracy@1 |
|
|
- type: cosine_accuracy@20 |
|
|
value: 0.8725949037961519 |
|
|
name: Cosine Accuracy@20 |
|
|
- type: cosine_accuracy@50 |
|
|
value: 0.9297971918876755 |
|
|
name: Cosine Accuracy@50 |
|
|
- type: cosine_accuracy@100 |
|
|
value: 0.9552782111284451 |
|
|
name: Cosine Accuracy@100 |
|
|
- type: cosine_accuracy@150 |
|
|
value: 0.968278731149246 |
|
|
name: Cosine Accuracy@150 |
|
|
- type: cosine_accuracy@200 |
|
|
value: 0.9729589183567343 |
|
|
name: Cosine Accuracy@200 |
|
|
- type: cosine_precision@1 |
|
|
value: 0.5429017160686428 |
|
|
name: Cosine Precision@1 |
|
|
- type: cosine_precision@20 |
|
|
value: 0.10709828393135724 |
|
|
name: Cosine Precision@20 |
|
|
- type: cosine_precision@50 |
|
|
value: 0.04726989079563183 |
|
|
name: Cosine Precision@50 |
|
|
- type: cosine_precision@100 |
|
|
value: 0.025002600104004166 |
|
|
name: Cosine Precision@100 |
|
|
- type: cosine_precision@150 |
|
|
value: 0.01712601837406829 |
|
|
name: Cosine Precision@150 |
|
|
- type: cosine_precision@200 |
|
|
value: 0.013044721788871557 |
|
|
name: Cosine Precision@200 |
|
|
- type: cosine_recall@1 |
|
|
value: 0.20383948691280984 |
|
|
name: Cosine Recall@1 |
|
|
- type: cosine_recall@20 |
|
|
value: 0.7817386028774485 |
|
|
name: Cosine Recall@20 |
|
|
- type: cosine_recall@50 |
|
|
value: 0.8605044201768071 |
|
|
name: Cosine Recall@50 |
|
|
- type: cosine_recall@100 |
|
|
value: 0.9077223088923557 |
|
|
name: Cosine Recall@100 |
|
|
- type: cosine_recall@150 |
|
|
value: 0.9319032761310452 |
|
|
name: Cosine Recall@150 |
|
|
- type: cosine_recall@200 |
|
|
value: 0.9461778471138845 |
|
|
name: Cosine Recall@200 |
|
|
- type: cosine_ndcg@1 |
|
|
value: 0.5429017160686428 |
|
|
name: Cosine Ndcg@1 |
|
|
- type: cosine_ndcg@20 |
|
|
value: 0.6364696194038222 |
|
|
name: Cosine Ndcg@20 |
|
|
- type: cosine_ndcg@50 |
|
|
value: 0.6580204683537704 |
|
|
name: Cosine Ndcg@50 |
|
|
- type: cosine_ndcg@100 |
|
|
value: 0.6686859699628315 |
|
|
name: Cosine Ndcg@100 |
|
|
- type: cosine_ndcg@150 |
|
|
value: 0.6734670399055159 |
|
|
name: Cosine Ndcg@150 |
|
|
- type: cosine_ndcg@200 |
|
|
value: 0.6761041848609185 |
|
|
name: Cosine Ndcg@200 |
|
|
- type: cosine_mrr@1 |
|
|
value: 0.5429017160686428 |
|
|
name: Cosine Mrr@1 |
|
|
- type: cosine_mrr@20 |
|
|
value: 0.6331176720726237 |
|
|
name: Cosine Mrr@20 |
|
|
- type: cosine_mrr@50 |
|
|
value: 0.6350347522721764 |
|
|
name: Cosine Mrr@50 |
|
|
- type: cosine_mrr@100 |
|
|
value: 0.6354157777188323 |
|
|
name: Cosine Mrr@100 |
|
|
- type: cosine_mrr@150 |
|
|
value: 0.6355194502419383 |
|
|
name: Cosine Mrr@150 |
|
|
- type: cosine_mrr@200 |
|
|
value: 0.635546462249249 |
|
|
name: Cosine Mrr@200 |
|
|
- type: cosine_map@1 |
|
|
value: 0.5429017160686428 |
|
|
name: Cosine Map@1 |
|
|
- type: cosine_map@20 |
|
|
value: 0.546038259426052 |
|
|
name: Cosine Map@20 |
|
|
- type: cosine_map@50 |
|
|
value: 0.5513401593649401 |
|
|
name: Cosine Map@50 |
|
|
- type: cosine_map@100 |
|
|
value: 0.5528890114435938 |
|
|
name: Cosine Map@100 |
|
|
- type: cosine_map@150 |
|
|
value: 0.5533285819634786 |
|
|
name: Cosine Map@150 |
|
|
- type: cosine_map@200 |
|
|
value: 0.5535297820757661 |
|
|
name: Cosine Map@200 |
|
|
- type: cosine_map@500 |
|
|
value: 0.5538215020153545 |
|
|
name: Cosine Map@500 |
|
|
- task: |
|
|
type: information-retrieval |
|
|
name: Information Retrieval |
|
|
dataset: |
|
|
name: mix zh |
|
|
type: mix_zh |
|
|
metrics: |
|
|
- type: cosine_accuracy@1 |
|
|
value: 0.5751565762004175 |
|
|
name: Cosine Accuracy@1 |
|
|
- type: cosine_accuracy@20 |
|
|
value: 0.9514613778705637 |
|
|
name: Cosine Accuracy@20 |
|
|
- type: cosine_accuracy@50 |
|
|
value: 0.975991649269311 |
|
|
name: Cosine Accuracy@50 |
|
|
- type: cosine_accuracy@100 |
|
|
value: 0.9848643006263048 |
|
|
name: Cosine Accuracy@100 |
|
|
- type: cosine_accuracy@150 |
|
|
value: 0.9895615866388309 |
|
|
name: Cosine Accuracy@150 |
|
|
- type: cosine_accuracy@200 |
|
|
value: 0.9916492693110647 |
|
|
name: Cosine Accuracy@200 |
|
|
- type: cosine_precision@1 |
|
|
value: 0.5751565762004175 |
|
|
name: Cosine Precision@1 |
|
|
- type: cosine_precision@20 |
|
|
value: 0.123982254697286 |
|
|
name: Cosine Precision@20 |
|
|
- type: cosine_precision@50 |
|
|
value: 0.05465553235908143 |
|
|
name: Cosine Precision@50 |
|
|
- type: cosine_precision@100 |
|
|
value: 0.02851252609603341 |
|
|
name: Cosine Precision@100 |
|
|
- type: cosine_precision@150 |
|
|
value: 0.019324982602644397 |
|
|
name: Cosine Precision@150 |
|
|
- type: cosine_precision@200 |
|
|
value: 0.014634655532359089 |
|
|
name: Cosine Precision@200 |
|
|
- type: cosine_recall@1 |
|
|
value: 0.19298513768764292 |
|
|
name: Cosine Recall@1 |
|
|
- type: cosine_recall@20 |
|
|
value: 0.8174060542797494 |
|
|
name: Cosine Recall@20 |
|
|
- type: cosine_recall@50 |
|
|
value: 0.901000347947112 |
|
|
name: Cosine Recall@50 |
|
|
- type: cosine_recall@100 |
|
|
value: 0.9399095337508698 |
|
|
name: Cosine Recall@100 |
|
|
- type: cosine_recall@150 |
|
|
value: 0.9558716075156575 |
|
|
name: Cosine Recall@150 |
|
|
- type: cosine_recall@200 |
|
|
value: 0.965196590118302 |
|
|
name: Cosine Recall@200 |
|
|
- type: cosine_ndcg@1 |
|
|
value: 0.5751565762004175 |
|
|
name: Cosine Ndcg@1 |
|
|
- type: cosine_ndcg@20 |
|
|
value: 0.6621196118161056 |
|
|
name: Cosine Ndcg@20 |
|
|
- type: cosine_ndcg@50 |
|
|
value: 0.6858570871515306 |
|
|
name: Cosine Ndcg@50 |
|
|
- type: cosine_ndcg@100 |
|
|
value: 0.6947962879201968 |
|
|
name: Cosine Ndcg@100 |
|
|
- type: cosine_ndcg@150 |
|
|
value: 0.6980250427797421 |
|
|
name: Cosine Ndcg@150 |
|
|
- type: cosine_ndcg@200 |
|
|
value: 0.6997922044919449 |
|
|
name: Cosine Ndcg@200 |
|
|
- type: cosine_mrr@1 |
|
|
value: 0.5751565762004175 |
|
|
name: Cosine Mrr@1 |
|
|
- type: cosine_mrr@20 |
|
|
value: 0.6974988781113621 |
|
|
name: Cosine Mrr@20 |
|
|
- type: cosine_mrr@50 |
|
|
value: 0.6983413027160801 |
|
|
name: Cosine Mrr@50 |
|
|
- type: cosine_mrr@100 |
|
|
value: 0.6984820179753005 |
|
|
name: Cosine Mrr@100 |
|
|
- type: cosine_mrr@150 |
|
|
value: 0.6985228351798531 |
|
|
name: Cosine Mrr@150 |
|
|
- type: cosine_mrr@200 |
|
|
value: 0.6985351624205532 |
|
|
name: Cosine Mrr@200 |
|
|
- type: cosine_map@1 |
|
|
value: 0.5751565762004175 |
|
|
name: Cosine Map@1 |
|
|
- type: cosine_map@20 |
|
|
value: 0.5395939445358217 |
|
|
name: Cosine Map@20 |
|
|
- type: cosine_map@50 |
|
|
value: 0.5465541726714618 |
|
|
name: Cosine Map@50 |
|
|
- type: cosine_map@100 |
|
|
value: 0.5480058234906587 |
|
|
name: Cosine Map@100 |
|
|
- type: cosine_map@150 |
|
|
value: 0.5483452539266979 |
|
|
name: Cosine Map@150 |
|
|
- type: cosine_map@200 |
|
|
value: 0.548487754480418 |
|
|
name: Cosine Map@200 |
|
|
- type: cosine_map@500 |
|
|
value: 0.5486704400924459 |
|
|
name: Cosine Map@500 |
|
|
--- |
|
|
|
|
|
# SentenceTransformer |
|
|
|
|
|
This is a [sentence-transformers](https://www.SBERT.net) model trained. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more. |
|
|
|
|
|
## Model Details |
|
|
|
|
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### Model Description |
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- **Model Type:** Sentence Transformer |
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<!-- - **Base model:** [Unknown](https://huggingface.co/unknown) --> |
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- **Maximum Sequence Length:** 512 tokens |
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- **Output Dimensionality:** 768 dimensions |
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- **Similarity Function:** Cosine Similarity |
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<!-- - **Training Dataset:** Unknown --> |
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<!-- - **Language:** Unknown --> |
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<!-- - **License:** Unknown --> |
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### Model Sources |
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- **Documentation:** [Sentence Transformers Documentation](https://sbert.net) |
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- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers) |
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- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers) |
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### Full Model Architecture |
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``` |
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SentenceTransformer( |
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(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: NewModel |
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(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) |
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(2): Normalize() |
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) |
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``` |
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## Usage |
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### Direct Usage (Sentence Transformers) |
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First install the Sentence Transformers library: |
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```bash |
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pip install -U sentence-transformers |
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``` |
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Then you can load this model and run inference. |
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```python |
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from sentence_transformers import SentenceTransformer |
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# Download from the 🤗 Hub |
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model = SentenceTransformer("sentence_transformers_model_id") |
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# Run inference |
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sentences = [ |
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'Entwicklerin für mobile Anwendungen', |
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'Mergers-and-Acquisitions-Analyst/Mergers-and-Acquisitions-Analystin', |
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'fashion design expert', |
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] |
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embeddings = model.encode(sentences) |
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print(embeddings.shape) |
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# [3, 768] |
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# Get the similarity scores for the embeddings |
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similarities = model.similarity(embeddings, embeddings) |
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print(similarities.shape) |
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# [3, 3] |
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``` |
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<!-- |
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### Direct Usage (Transformers) |
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<details><summary>Click to see the direct usage in Transformers</summary> |
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</details> |
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--> |
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<!-- |
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### Downstream Usage (Sentence Transformers) |
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You can finetune this model on your own dataset. |
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<details><summary>Click to expand</summary> |
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</details> |
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--> |
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<!-- |
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### Out-of-Scope Use |
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*List how the model may foreseeably be misused and address what users ought not to do with the model.* |
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--> |
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## Evaluation |
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### Metrics |
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#### Information Retrieval |
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* Datasets: `full_en`, `full_es`, `full_de`, `full_zh`, `mix_es`, `mix_de` and `mix_zh` |
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* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator) |
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| Metric | full_en | full_es | full_de | full_zh | mix_es | mix_de | mix_zh | |
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|:---------------------|:-----------|:-----------|:-----------|:-----------|:-----------|:-----------|:-----------| |
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| cosine_accuracy@1 | 0.6286 | 0.1135 | 0.2956 | 0.6505 | 0.6173 | 0.5429 | 0.5752 | |
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| cosine_accuracy@20 | 0.9714 | 1.0 | 0.9606 | 0.9709 | 0.9033 | 0.8726 | 0.9515 | |
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| cosine_accuracy@50 | 0.9905 | 1.0 | 0.9803 | 0.9806 | 0.9444 | 0.9298 | 0.976 | |
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| cosine_accuracy@100 | 0.9905 | 1.0 | 0.9852 | 0.9903 | 0.9704 | 0.9553 | 0.9849 | |
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| cosine_accuracy@150 | 0.9905 | 1.0 | 0.9852 | 0.9903 | 0.9813 | 0.9683 | 0.9896 | |
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| cosine_accuracy@200 | 0.9905 | 1.0 | 0.9901 | 0.9903 | 0.986 | 0.973 | 0.9916 | |
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| cosine_precision@1 | 0.6286 | 0.1135 | 0.2956 | 0.6505 | 0.6173 | 0.5429 | 0.5752 | |
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| cosine_precision@20 | 0.4724 | 0.5214 | 0.4244 | 0.4461 | 0.1097 | 0.1071 | 0.124 | |
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| cosine_precision@50 | 0.2838 | 0.3389 | 0.2906 | 0.2693 | 0.0479 | 0.0473 | 0.0547 | |
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| cosine_precision@100 | 0.1707 | 0.2141 | 0.1902 | 0.166 | 0.0252 | 0.025 | 0.0285 | |
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| cosine_precision@150 | 0.1229 | 0.161 | 0.1448 | 0.12 | 0.0172 | 0.0171 | 0.0193 | |
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| cosine_precision@200 | 0.097 | 0.1309 | 0.1178 | 0.0948 | 0.013 | 0.013 | 0.0146 | |
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| cosine_recall@1 | 0.0657 | 0.0035 | 0.0111 | 0.0613 | 0.238 | 0.2038 | 0.193 | |
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| cosine_recall@20 | 0.5041 | 0.3483 | 0.2624 | 0.4798 | 0.8149 | 0.7817 | 0.8174 | |
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| cosine_recall@50 | 0.6763 | 0.5044 | 0.3999 | 0.6511 | 0.8867 | 0.8605 | 0.901 | |
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| cosine_recall@100 | 0.7798 | 0.5963 | 0.5012 | 0.7667 | 0.9332 | 0.9077 | 0.9399 | |
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| cosine_recall@150 | 0.8312 | 0.654 | 0.5599 | 0.8234 | 0.9536 | 0.9319 | 0.9559 | |
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| cosine_recall@200 | 0.8655 | 0.7028 | 0.602 | 0.8571 | 0.9652 | 0.9462 | 0.9652 | |
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| cosine_ndcg@1 | 0.6286 | 0.1135 | 0.2956 | 0.6505 | 0.6173 | 0.5429 | 0.5752 | |
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| cosine_ndcg@20 | 0.6385 | 0.5638 | 0.4646 | 0.6163 | 0.6864 | 0.6365 | 0.6621 | |
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| cosine_ndcg@50 | 0.6505 | 0.5286 | 0.4364 | 0.6306 | 0.706 | 0.658 | 0.6859 | |
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| cosine_ndcg@100 | 0.701 | 0.5495 | 0.4594 | 0.6853 | 0.7161 | 0.6687 | 0.6948 | |
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| cosine_ndcg@150 | 0.7229 | 0.5779 | 0.4887 | 0.7088 | 0.7201 | 0.6735 | 0.698 | |
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| **cosine_ndcg@200** | **0.7371** | **0.6002** | **0.5085** | **0.7228** | **0.7222** | **0.6761** | **0.6998** | |
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| cosine_mrr@1 | 0.6286 | 0.1135 | 0.2956 | 0.6505 | 0.6173 | 0.5429 | 0.5752 | |
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| cosine_mrr@20 | 0.7791 | 0.55 | 0.5034 | 0.7939 | 0.6921 | 0.6331 | 0.6975 | |
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| cosine_mrr@50 | 0.7798 | 0.55 | 0.5041 | 0.7941 | 0.6935 | 0.635 | 0.6983 | |
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| cosine_mrr@100 | 0.7798 | 0.55 | 0.5042 | 0.7943 | 0.6939 | 0.6354 | 0.6985 | |
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| cosine_mrr@150 | 0.7798 | 0.55 | 0.5042 | 0.7943 | 0.694 | 0.6355 | 0.6985 | |
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| cosine_mrr@200 | 0.7798 | 0.55 | 0.5042 | 0.7943 | 0.694 | 0.6355 | 0.6985 | |
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| cosine_map@1 | 0.6286 | 0.1135 | 0.2956 | 0.6505 | 0.6173 | 0.5429 | 0.5752 | |
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| cosine_map@20 | 0.4949 | 0.4321 | 0.3326 | 0.4673 | 0.6028 | 0.546 | 0.5396 | |
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| cosine_map@50 | 0.4754 | 0.3662 | 0.278 | 0.4492 | 0.608 | 0.5513 | 0.5466 | |
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| cosine_map@100 | 0.5028 | 0.3676 | 0.2753 | 0.476 | 0.6094 | 0.5529 | 0.548 | |
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| cosine_map@150 | 0.5109 | 0.3791 | 0.2859 | 0.4843 | 0.6098 | 0.5533 | 0.5483 | |
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| cosine_map@200 | 0.5152 | 0.3864 | 0.2919 | 0.4885 | 0.6099 | 0.5535 | 0.5485 | |
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| cosine_map@500 | 0.5212 | 0.3967 | 0.3038 | 0.4949 | 0.6101 | 0.5538 | 0.5487 | |
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<!-- |
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## Bias, Risks and Limitations |
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*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.* |
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--> |
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<!-- |
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### Recommendations |
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*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.* |
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--> |
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## Training Details |
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### Training Dataset |
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#### Unnamed Dataset |
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* Size: 86,648 training samples |
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* Columns: <code>sentence</code> and <code>label</code> |
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* Approximate statistics based on the first 1000 samples: |
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| | sentence | label | |
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|:--------|:---------------------------------------------------------------------------------|:-------------------------------------| |
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| type | string | list | |
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| details | <ul><li>min: 2 tokens</li><li>mean: 8.25 tokens</li><li>max: 54 tokens</li></ul> | <ul><li>size: 768 elements</li></ul> | |
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* Samples: |
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| sentence | label | |
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|:-----------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------| |
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| <code></code> | <code>[-0.07171934843063354, 0.03595816716551781, -0.029780959710478783, 0.006593302357941866, 0.040611181408166885, ...]</code> | |
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| <code>airport environment officer</code> | <code>[-0.022075481712818146, 0.02999737113714218, -0.02189866080880165, 0.016531817615032196, 0.012234307825565338, ...]</code> | |
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| <code>Flake操作员</code> | <code>[-0.04815564677119255, 0.023524893447756767, -0.01583661139011383, 0.042527906596660614, 0.03815540298819542, ...]</code> | |
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* Loss: [<code>MSELoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#mseloss) |
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### Training Hyperparameters |
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#### Non-Default Hyperparameters |
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- `eval_strategy`: steps |
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- `per_device_train_batch_size`: 128 |
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- `per_device_eval_batch_size`: 128 |
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- `gradient_accumulation_steps`: 2 |
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- `learning_rate`: 0.0001 |
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- `num_train_epochs`: 5 |
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- `warmup_ratio`: 0.05 |
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- `log_on_each_node`: False |
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- `fp16`: True |
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- `dataloader_num_workers`: 4 |
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- `ddp_find_unused_parameters`: True |
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- `batch_sampler`: no_duplicates |
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#### All Hyperparameters |
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<details><summary>Click to expand</summary> |
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- `overwrite_output_dir`: False |
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- `do_predict`: False |
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- `eval_strategy`: steps |
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- `prediction_loss_only`: True |
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- `per_device_train_batch_size`: 128 |
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- `per_device_eval_batch_size`: 128 |
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- `per_gpu_train_batch_size`: None |
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- `per_gpu_eval_batch_size`: None |
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- `gradient_accumulation_steps`: 2 |
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- `eval_accumulation_steps`: None |
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- `torch_empty_cache_steps`: None |
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- `learning_rate`: 0.0001 |
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- `weight_decay`: 0.0 |
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- `adam_beta1`: 0.9 |
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- `adam_beta2`: 0.999 |
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- `adam_epsilon`: 1e-08 |
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- `max_grad_norm`: 1.0 |
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- `num_train_epochs`: 5 |
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- `max_steps`: -1 |
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- `lr_scheduler_type`: linear |
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- `lr_scheduler_kwargs`: {} |
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- `warmup_ratio`: 0.05 |
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- `warmup_steps`: 0 |
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- `log_level`: passive |
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- `log_level_replica`: warning |
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- `log_on_each_node`: False |
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- `logging_nan_inf_filter`: True |
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- `save_safetensors`: True |
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- `save_on_each_node`: False |
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- `save_only_model`: False |
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- `restore_callback_states_from_checkpoint`: False |
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- `no_cuda`: False |
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- `use_cpu`: False |
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- `use_mps_device`: False |
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- `seed`: 42 |
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- `data_seed`: None |
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- `jit_mode_eval`: False |
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- `use_ipex`: False |
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- `bf16`: False |
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- `fp16`: True |
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- `fp16_opt_level`: O1 |
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- `half_precision_backend`: auto |
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- `bf16_full_eval`: False |
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- `fp16_full_eval`: False |
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- `tf32`: None |
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- `local_rank`: 0 |
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- `ddp_backend`: None |
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- `tpu_num_cores`: None |
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- `tpu_metrics_debug`: False |
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- `debug`: [] |
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- `dataloader_drop_last`: True |
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- `dataloader_num_workers`: 4 |
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- `dataloader_prefetch_factor`: None |
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- `past_index`: -1 |
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- `disable_tqdm`: False |
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- `remove_unused_columns`: True |
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- `label_names`: None |
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- `load_best_model_at_end`: False |
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- `ignore_data_skip`: False |
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- `fsdp`: [] |
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- `fsdp_min_num_params`: 0 |
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- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False} |
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- `tp_size`: 0 |
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- `fsdp_transformer_layer_cls_to_wrap`: None |
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- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None} |
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- `deepspeed`: None |
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- `label_smoothing_factor`: 0.0 |
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- `optim`: adamw_torch |
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- `optim_args`: None |
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- `adafactor`: False |
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- `group_by_length`: False |
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- `length_column_name`: length |
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- `ddp_find_unused_parameters`: True |
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- `ddp_bucket_cap_mb`: None |
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- `ddp_broadcast_buffers`: False |
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- `dataloader_pin_memory`: True |
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- `dataloader_persistent_workers`: False |
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- `skip_memory_metrics`: True |
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- `use_legacy_prediction_loop`: False |
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- `push_to_hub`: False |
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- `resume_from_checkpoint`: None |
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- `hub_model_id`: None |
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- `hub_strategy`: every_save |
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- `hub_private_repo`: None |
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- `hub_always_push`: False |
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- `gradient_checkpointing`: False |
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- `gradient_checkpointing_kwargs`: None |
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- `include_inputs_for_metrics`: False |
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- `include_for_metrics`: [] |
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- `eval_do_concat_batches`: True |
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- `fp16_backend`: auto |
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- `push_to_hub_model_id`: None |
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- `push_to_hub_organization`: None |
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- `mp_parameters`: |
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- `auto_find_batch_size`: False |
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- `full_determinism`: False |
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- `torchdynamo`: None |
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- `ray_scope`: last |
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- `ddp_timeout`: 1800 |
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- `torch_compile`: False |
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- `torch_compile_backend`: None |
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- `torch_compile_mode`: None |
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- `include_tokens_per_second`: False |
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- `include_num_input_tokens_seen`: False |
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- `neftune_noise_alpha`: None |
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- `optim_target_modules`: None |
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- `batch_eval_metrics`: False |
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- `eval_on_start`: False |
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- `use_liger_kernel`: False |
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- `eval_use_gather_object`: False |
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- `average_tokens_across_devices`: False |
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- `prompts`: None |
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- `batch_sampler`: no_duplicates |
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- `multi_dataset_batch_sampler`: proportional |
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</details> |
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### Training Logs |
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| Epoch | Step | Training Loss | full_en_cosine_ndcg@200 | full_es_cosine_ndcg@200 | full_de_cosine_ndcg@200 | full_zh_cosine_ndcg@200 | mix_es_cosine_ndcg@200 | mix_de_cosine_ndcg@200 | mix_zh_cosine_ndcg@200 | |
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|:------:|:----:|:-------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:----------------------:|:----------------------:|:----------------------:| |
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| -1 | -1 | - | 0.5348 | 0.4311 | 0.3678 | 0.5333 | 0.2580 | 0.1924 | 0.2871 | |
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| 0.0030 | 1 | 0.0017 | - | - | - | - | - | - | - | |
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| 0.2959 | 100 | 0.001 | - | - | - | - | - | - | - | |
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| 0.5917 | 200 | 0.0005 | 0.6702 | 0.5287 | 0.4566 | 0.6809 | 0.5864 | 0.5302 | 0.4739 | |
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| 0.8876 | 300 | 0.0004 | - | - | - | - | - | - | - | |
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| 1.1834 | 400 | 0.0004 | 0.7057 | 0.5643 | 0.4790 | 0.7033 | 0.6604 | 0.6055 | 0.6003 | |
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| 1.4793 | 500 | 0.0004 | - | - | - | - | - | - | - | |
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| 1.7751 | 600 | 0.0003 | 0.7184 | 0.5783 | 0.4910 | 0.7127 | 0.6927 | 0.6416 | 0.6485 | |
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| 2.0710 | 700 | 0.0003 | - | - | - | - | - | - | - | |
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| 2.3669 | 800 | 0.0003 | 0.7307 | 0.5938 | 0.5023 | 0.7233 | 0.7125 | 0.6639 | 0.6847 | |
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| 2.6627 | 900 | 0.0003 | - | - | - | - | - | - | - | |
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| 2.9586 | 1000 | 0.0003 | 0.7371 | 0.6002 | 0.5085 | 0.7228 | 0.7222 | 0.6761 | 0.6998 | |
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### Framework Versions |
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- Python: 3.11.11 |
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- Sentence Transformers: 4.1.0 |
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- Transformers: 4.51.3 |
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- PyTorch: 2.6.0+cu124 |
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- Accelerate: 1.6.0 |
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- Datasets: 3.5.0 |
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- Tokenizers: 0.21.1 |
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## Citation |
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### BibTeX |
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#### Sentence Transformers |
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```bibtex |
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@inproceedings{reimers-2019-sentence-bert, |
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title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks", |
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author = "Reimers, Nils and Gurevych, Iryna", |
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booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing", |
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month = "11", |
|
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year = "2019", |
|
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publisher = "Association for Computational Linguistics", |
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url = "https://arxiv.org/abs/1908.10084", |
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} |
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``` |
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#### MSELoss |
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```bibtex |
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@inproceedings{reimers-2020-multilingual-sentence-bert, |
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title = "Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation", |
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author = "Reimers, Nils and Gurevych, Iryna", |
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booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing", |
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month = "11", |
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year = "2020", |
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publisher = "Association for Computational Linguistics", |
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url = "https://arxiv.org/abs/2004.09813", |
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} |
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``` |
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