readme: ---
  language:
  - en
  tags:
  - generated_from_trainer
  datasets:
  - glue
  model-index:
  - name: debug
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # BioLinkBERT-large-mnli
  
  This model is a fine-tuned version of [BioLinkBERT-large](https://huggingface.co/michiyasunaga/BioLinkBERT-large) on the GLUE [MNLI](https://huggingface.co/datasets/multi_nli) dataset.
  
  The results are 
  
  | **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 | MNLI dev mm | 85.19   |
  |                        | MNLI dev m  | 84.96   |
  |                        | SNLI test   | 78.959  |
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 3e-05
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.5
  - num_epochs: 10.0
  - mixed_precision_training: Native AMP
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1