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
Runs of AdrienB134 ColBERTv2.0-spanish-mmarcoES on huggingface.co
23
Total runs
-1
24-hour runs
-2
3-day runs
0
7-day runs
4
30-day runs
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