The model uses the original
scivocab
wordpiece vocabulary and was trained using the
average pooling strategy
and a
softmax loss
.
Base model
:
allenai/scibert-scivocab-cased
from HuggingFace's
AutoModel
.
Training time
: ~4 hours on the NVIDIA Tesla P100 GPU provided in Kaggle Notebooks.
Parameters
:
Parameter
Value
Batch size
64
Training steps
20000
Warmup steps
1450
Lowercasing
True
Max. Seq. Length
128
Performances
: The performance was evaluated on the test portion of the
STS dataset
using Spearman rank correlation and compared to the performances of a general BERT base model obtained with the same procedure to verify their similarity.
Model
Score
scibert-nli
(this)
74.50
bert-base-nli-mean-tokens
[3]
77.12
An example usage for similarity-based scientific paper retrieval is provided in the
Covid Papers Browser
repository.
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