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This model is developed with transformers v4.9.1.
```
m = 0.8444
eval_samples = 9815
mm = 0.8495
eval_samples = 9832
```
# Train
```bash
#!/usr/bin/env bash
export CUDA_VISIBLE_DEVICES=0
OUTDIR=bert-mnli
NEPOCH=3
WORKDIR=transformers/examples/pytorch/text-classification
cd $WORKDIR
python run_glue.py \
--model_name_or_path bert-base-uncased \
--task_name mnli \
--max_seq_length 128 \
--do_train \
--per_device_train_batch_size 32 \
--learning_rate 2e-5 \
--num_train_epochs $NEPOCH \
--logging_steps 1 \
--evaluation_strategy steps \
--save_steps 3000 \
--do_eval \
--per_device_eval_batch_size 128 \
--eval_steps 250 \
--output_dir $OUTDIR
--overwrite_output_dir
```
# Eval
```bash
export CUDA_VISIBLE_DEVICES=0
OUTDIR=eval-bert-mnli
WORKDIR=transformers/examples/pytorch/text-classification
cd $WORKDIR
nohup python run_glue.py \
--model_name_or_path vuiseng9/bert-mnli \
--task_name mnli \
--do_eval \
--per_device_eval_batch_size 128 \
--max_seq_length 128 \
--overwrite_output_dir \
--output_dir $OUTDIR 2>&1 | tee $OUTDIR/run.log &
```
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