wangchanberta-base-att-spm-uncased-finetune-qa
Finetuning wangchanberta-base-att-spm-uncased
with the training set of iapp_wiki_qa_squad
and thaiqa
(removed examples which have cosine similarity with validation and test examples over 0.8). Benchmarks shared on wandb using validation and test sets of iapp_wiki_qa_squad
.
Trained with
export WANDB_PROJECT=wangchanberta-qa
export MODEL_NAME=wangchanberta-base-att-spm-uncased
python train_question_answering_lm_finetuning.py \
--model_name $MODEL_NAME \
--dataset_name iapp_thaiqa \
--output_dir $MODEL_NAME-finetune-iapp_thaiqa-model \
--log_dir $MODEL_NAME-finetune-iapp_thaiqa-log \
--lowercase \
--pad_on_right \
--fp16
export MODEL_NAME=xlm-roberta-base
python train_question_answering_lm_finetuning.py \
--model_name $MODEL_NAME \
--dataset_name iapp_thaiqa \
--output_dir $MODEL_NAME-finetune-iapp_thaiqa-model \
--log_dir $MODEL_NAME-finetune-iapp_thaiqa-log \
--model_max_length 416 \
--pad_on_right \
--fp16
export MODEL_NAME=bert-base-multilingual-cased
python train_question_answering_lm_finetuning.py \
--model_name $MODEL_NAME \
--dataset_name iapp_thaiqa \
--output_dir $MODEL_NAME-finetune-iapp_thaiqa-model \
--log_dir $MODEL_NAME-finetune-iapp_thaiqa-log \
--pad_on_right \
--fp16
export MODEL_NAME=wangchanberta-base-wiki-spm
python train_question_answering_lm_finetuning.py \
--model_name $MODEL_NAME \
--dataset_name iapp_thaiqa \
--output_dir $MODEL_NAME-finetune-iapp_thaiqa-model \
--log_dir $MODEL_NAME-finetune-iapp_thaiqa-log \
--pad_on_right \
--fp16