readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - elsevier-oa-cc-by
  model-index:
  - name: bert-base-uncased-finetuned-academic
    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. -->
  
  # bert-base-uncased-finetuned-academic
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the elsevier-oa-cc-by dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.5893
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 1e-05
  - train_batch_size: 40
  - eval_batch_size: 40
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.97) and epsilon=0.0001
  - lr_scheduler_type: linear
  - num_epochs: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 2.9591        | 0.25  | 820  | 2.6567          |
  | 2.7993        | 0.5   | 1640 | 2.6006          |
  | 2.7519        | 0.75  | 2460 | 2.5707          |
  | 2.7319        | 1.0   | 3280 | 2.5763          |
  | 2.7359        | 1.25  | 4100 | 2.5866          |
  | 2.7451        | 1.5   | 4920 | 2.5855          |
  | 2.7421        | 1.75  | 5740 | 2.5770          |
  | 2.7319        | 2.0   | 6560 | 2.5762          |
  | 2.7356        | 2.25  | 7380 | 2.5807          |
  | 2.7376        | 2.5   | 8200 | 2.5813          |
  | 2.7386        | 2.75  | 9020 | 2.5841          |
  | 2.7378        | 3.0   | 9840 | 2.5737          |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  