SUMIN/HuggingFace_transformer
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per_device instead of per_gpu/error thrown when argument unknown (#4618)

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* per_device instead of per_gpu/error thrown when argument unknown

* [docs] Restore examples.md symlink

* Correct absolute links so that symlink to the doc works correctly

* Update src/transformers/hf_argparser.py

Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Warning + reorder

* Docs

* Style

* not for squad

Co-authored-by: Julien Chaumond <chaumond@gmail.com>
This commit is contained in:
Lysandre Debut
2020-05-27 11:36:55 -04:00
committed by GitHub
parent 1381b6d01d
commit 6a17688021
10 changed files with 73 additions and 686 deletions
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16
README.md
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@@ -340,8 +340,8 @@ python ./examples/text-classification/run_glue.py \
--do_eval \
--data_dir $GLUE_DIR/$TASK_NAME \
--max_seq_length 128 \
--per_gpu_eval_batch_size=8 \
--per_gpu_train_batch_size=8 \
--per_device_eval_batch_size=8 \
--per_device_train_batch_size=8 \
--learning_rate 2e-5 \
--num_train_epochs 3.0 \
--output_dir /tmp/$TASK_NAME/
@@ -367,8 +367,8 @@ python ./examples/text-classification/run_glue.py \
--data_dir=${GLUE_DIR}/STS-B \
--output_dir=./proc_data/sts-b-110 \
--max_seq_length=128 \
--per_gpu_eval_batch_size=8 \
--per_gpu_train_batch_size=8 \
--per_device_eval_batch_size=8 \
--per_device_train_batch_size=8 \
--gradient_accumulation_steps=1 \
--max_steps=1200 \
--model_name=xlnet-large-cased \
@@ -391,8 +391,8 @@ python -m torch.distributed.launch --nproc_per_node 8 ./examples/text-classifica
--do_eval \
--data_dir $GLUE_DIR/MRPC/ \
--max_seq_length 128 \
--per_gpu_eval_batch_size=8 \
--per_gpu_train_batch_size=8 \
--per_device_eval_batch_size=8 \
--per_device_train_batch_size=8 \
--learning_rate 2e-5 \
--num_train_epochs 3.0 \
--output_dir /tmp/mrpc_output/ \
@@ -428,8 +428,8 @@ python -m torch.distributed.launch --nproc_per_node=8 ./examples/question-answer
--max_seq_length 384 \
--doc_stride 128 \
--output_dir ../models/wwm_uncased_finetuned_squad/ \
--per_gpu_eval_batch_size=3 \
--per_gpu_train_batch_size=3 \
--per_device_eval_batch_size=3 \
--per_device_train_batch_size=3 \
```
Training with these hyper-parameters gave us the following results: