AdrienB134/ColBERTv2.0-spanish-mmarcoES

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).