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 1 Tesla L4 GPU with 24GBs of memory 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 80 hours.

Data

The model is fine-tuned on the French 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-fr, 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@200
ColBERTv2.0-mmarcoFR french 110M 440MB 32.76 76.93 81.74
Downloads last month
37
Safetensors
Model size
111M params
Tensor type
F32
·
Unable to determine this model’s pipeline type. Check the docs .

Dataset used to train AdrienB134/ColBERTv2.0-mmarcoFR

Collection including AdrienB134/ColBERTv2.0-mmarcoFR