Text Retrieval
sentence-transformers
Safetensors
Amharic
xlm-roberta
sparse-encoder
sparse
splade
Generated from Trainer
dataset_size:245876
loss:SpladeLoss
loss:SparseMultipleNegativesRankingLoss
loss:FlopsLoss
Eval Results (legacy)
Instructions to use rasyosef/splade-amharic-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rasyosef/splade-amharic-medium with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rasyosef/splade-amharic-medium") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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library_name: sentence-transformers
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license: mit
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metrics:
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- dot_accuracy@1
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- dot_accuracy@3
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- dot_accuracy@5
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- dot_accuracy@10
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- dot_precision@1
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- dot_precision@3
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- dot_precision@5
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- dot_recall@1
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- dot_recall@3
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- dot_recall@5
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- dot_recall@10
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- dot_ndcg@10
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- dot_mrr@10
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- dot_map@100
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- query_active_dims
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- query_sparsity_ratio
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- corpus_active_dims
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name: Amharic Passage Retrieval Dataset V2
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type: rasyosef/Amharic-Passage-Retrieval-Dataset-V2
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metrics:
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- type: dot_accuracy@1
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value: 0.6285881663737551
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name: Dot Accuracy@1
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- type: dot_accuracy@3
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value: 0.8107791446983011
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name: Dot Accuracy@3
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- type: dot_accuracy@5
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value: 0.8580843585237259
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name: Dot Accuracy@5
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- type: dot_accuracy@10
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value: 0.895577035735208
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name: Dot Accuracy@10
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- type: dot_precision@1
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value: 0.6285881663737551
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name: Dot Precision@1
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- type: dot_precision@3
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value: 0.2702597148994337
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name: Dot Precision@3
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- type: dot_precision@5
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value: 0.17161687170474518
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name: Dot Precision@5
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- type: dot_precision@10
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value: 0.0895577035735208
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name: Dot Precision@10
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- type: dot_recall@1
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value: 0.6285881663737551
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name: Dot Recall@1
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- type: dot_recall@3
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value: 0.8107791446983011
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name: Dot Recall@3
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- type: dot_recall@5
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value: 0.8580843585237259
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name: Dot Recall@5
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- type: dot_mrr@10
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value: 0.7282295240884877
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name: Dot Mrr@10
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- type: dot_map@100
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value: 0.731417730197726
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name: Dot Map@100
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- type: query_active_dims
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value: 60.95884704589844
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name: Query Active Dims
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| Metric | Value |
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| dot_accuracy@1 | 0.6286 |
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| dot_accuracy@3 | 0.8108 |
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| dot_accuracy@5 | 0.8581 |
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| dot_accuracy@10 | 0.8956 |
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| dot_precision@1 | 0.6286 |
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| dot_precision@3 | 0.2703 |
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| dot_precision@5 | 0.1716 |
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| dot_precision@10 | 0.0896 |
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| dot_recall@1 | 0.6286 |
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| dot_recall@3 | 0.8108 |
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| dot_recall@5 | 0.8581 |
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| dot_recall@10 | 0.8956 |
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| **dot_ndcg@10** | **0.7694** |
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| dot_mrr@10 | 0.7282 |
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| dot_map@100 | 0.7314 |
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| query_active_dims | 60.9588 |
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| query_sparsity_ratio | 0.9981 |
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| corpus_active_dims | 117.9303 |
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library_name: sentence-transformers
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license: mit
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metrics:
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- dot_recall@5
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- dot_recall@10
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- dot_ndcg@10
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- dot_mrr@10
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- query_active_dims
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- query_sparsity_ratio
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- corpus_active_dims
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name: Amharic Passage Retrieval Dataset V2
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type: rasyosef/Amharic-Passage-Retrieval-Dataset-V2
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metrics:
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- type: dot_recall@5
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value: 0.8580843585237259
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name: Dot Recall@5
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- type: dot_mrr@10
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value: 0.7282295240884877
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name: Dot Mrr@10
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- type: query_active_dims
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value: 60.95884704589844
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name: Query Active Dims
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| Metric | Value |
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|:----------------------|:-----------|
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| dot_recall@5 | 0.8581 |
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| dot_recall@10 | 0.8956 |
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| **dot_ndcg@10** | **0.7694** |
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| dot_mrr@10 | 0.7282 |
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| query_active_dims | 60.9588 |
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| query_sparsity_ratio | 0.9981 |
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| corpus_active_dims | 117.9303 |
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