biolinkbert-large-mnli-resampled

This model is a fine-tuned version of BioLinkBERT-large on the resampled version of GLUE MNLI, i.e. cnut1648/mnli_resampled_as_mednli.

The performance is reported below:

Model	Dataset	Acc
Roberta-large-mnli	MNLI dev mm	90.12
	MNLI dev m	90.59
	SNLI test	88.25
BioLinkBERT-large	MNLI dev mm	33.56
	MNLI dev m	33.18
	SNLI test	32.66
BioLinkBERT-large-mnli-snli	MNLI dev mm	85.75
	MNLI dev m	85.30
	SNLI test	89.82
BioLinkBERT-large-mnli-resampled	MNLI dev mm	80.22
	MNLI dev m	78.07
	SNLI test	71.33

Compared to cnut1648/biolinkbert-large-mnli-snli, this checkpoint is never trained on SNLI.

The labels are "0": "entailment", "1": "neutral", "2": "contradiction"

Training procedure

We follow the same training procedure as cnut1648/biolinkbert-large-mnli-snli.

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu117
• Datasets 2.4.0
• Tokenizers 0.12.1