readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - conll2003
  model-index:
  - name: scibert-lm-const-finetuned-20
    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. -->
  
  # scibert-lm-const-finetuned-20
  
  This model is a fine-tuned version of [allenai/scibert_scivocab_cased](https://huggingface.co/allenai/scibert_scivocab_cased) on the conll2003 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.0099
  
  ## 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: 2e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 3.6081        | 1.0   | 118  | 2.9156          |
  | 2.7954        | 2.0   | 236  | 2.5940          |
  | 2.5762        | 3.0   | 354  | 2.5017          |
  | 2.4384        | 4.0   | 472  | 2.3923          |
  | 2.3391        | 5.0   | 590  | 2.2996          |
  | 2.2417        | 6.0   | 708  | 2.3180          |
  | 2.2161        | 7.0   | 826  | 2.2336          |
  | 2.1918        | 8.0   | 944  | 2.2465          |
  | 2.1494        | 9.0   | 1062 | 2.1871          |
  | 2.1215        | 10.0  | 1180 | 2.1566          |
  | 2.1015        | 11.0  | 1298 | 2.1849          |
  | 2.05          | 12.0  | 1416 | 2.1092          |
  | 2.0653        | 13.0  | 1534 | 2.2221          |
  | 2.0261        | 14.0  | 1652 | 2.1572          |
  | 2.0117        | 15.0  | 1770 | 2.1452          |
  | 1.9845        | 16.0  | 1888 | 2.1433          |
  | 1.9791        | 17.0  | 2006 | 2.1225          |
  | 1.9979        | 18.0  | 2124 | 2.0777          |
  | 1.9688        | 19.0  | 2242 | 2.1765          |
  | 1.9873        | 20.0  | 2360 | 2.0099          |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  