Tevatron reranker

```
examples/reranker/reranker_train.py \
  --output_dir reranker_xlmr.bs-32.epoch-1.mmarco \
  --model_name_or_path xlm-roberta-large --save_steps 20000 --dataset_name crystina-z/mmarco-train:all --fp16 --per_device_train_batch_size 4 --gradient_accumulation_steps 8 --train_n_passages 8 --learning_rate 5e-6 --q_max_len 16 --p_max_len 128 --num_train_epochs 1 --logging_steps 500 --dataloader_num_workers 4 --overwrite_output_dir
```
{}
transformers pytorch xlm-roberta text-classification autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #xlm-roberta #text-classification #autotrain_compatible #endpoints_compatible #region-us 

Tevatron reranker


TAGS
#transformers #pytorch #xlm-roberta #text-classification #autotrain_compatible #endpoints_compatible #region-us 

TAGS
#transformers #pytorch #xlm-roberta #text-classification #autotrain_compatible #endpoints_compatible #region-us 
