ColBERT Models
Collection
A collection of ColBERT models finetuned for several languages
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5 items
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Updated
Training
Details
The model is initialized from the ColBERTv1.0-bert-based-spanish-mmarcoES checkpoint and trained using the ColBERTv2 style of training.
It was trained on 2 Tesla T4 GPU with 16GBs of memory each with 20k warmup steps warmup using a batch size of 64 and the AdamW optimizer with a constant learning rate of 1e-05.
Total training time was around 60 hours.
Data
The model is fine-tuned on the Spanish version of the mMARCO dataset, a multi-lingual machine-translated version of the MS MARCO dataset.
Evaluation
The model is evaluated on the smaller development set of mMARCO-es, which consists of 6,980 queries for a corpus of 8.8M candidate passages. We report the mean reciprocal rank (MRR) and recall at various cut-offs (R@k).
| model | Vocab. | #Param. | Size | MRR@10 | R@50 | R@1000 |
|---|---|---|---|---|---|---|
| ColBERTv2.0-spanish-mmarcoES | spanish | 110M | 440MB | 32.86 | 76.46 | 81.06 |
| ColBERTv1.0-bert-based-spanish-mmarcoES | spanish | 110M | 440MB | 24.70 | 59,23 | 63.86 |
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