Edit model card

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
Downloads last month
95,676
Safetensors
Model size
110M params
Tensor type
F32
·
Unable to determine this model’s pipeline type. Check the docs .

Dataset used to train AdrienB134/ColBERTv2.0-spanish-mmarcoES

Space using AdrienB134/ColBERTv2.0-spanish-mmarcoES 1

Collection including AdrienB134/ColBERTv2.0-spanish-mmarcoES