stanfordnlp/imdb
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How to use yujiepan/bert-base-uncased-imdb with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="yujiepan/bert-base-uncased-imdb") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("yujiepan/bert-base-uncased-imdb")
model = AutoModelForSequenceClassification.from_pretrained("yujiepan/bert-base-uncased-imdb")This model is a fine-tuned version of textattack/bert-base-uncased-imdb on the imdb dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
python run_glue.py \
--model_name_or_path textattack/bert-base-uncased-imdb \
--dataset_name imdb \
--do_train \
--do_eval \
--max_seq_length 384 \
--pad_to_max_length False \
--per_device_train_batch_size 32 \
--per_device_eval_batch_size 32 \
--fp16 \
--learning_rate 5e-5 \
--optim adamw_torch \
--num_train_epochs 3 \
--overwrite_output_dir \
--output_dir /tmp/bert-base-uncased-imdb
Note: run_glue.py is modified to set the "test" split as evaluation dataset.
Base model
textattack/bert-base-uncased-imdb