readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-base-uncased-offensive-lm-tapt
    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-offensive-lm-tapt
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0002
  
  ## 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: 0.0001
  - train_batch_size: 8
  - eval_batch_size: 28
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 5
  - num_epochs: 16
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 2.219         | 0.07  | 100  | 0.0728          |
  | 0.0358        | 0.13  | 200  | 0.0090          |
  | 0.0106        | 0.2   | 300  | 0.0033          |
  | 0.0056        | 0.26  | 400  | 0.0020          |
  | 0.0053        | 0.33  | 500  | 0.0015          |
  | 0.003         | 0.39  | 600  | 0.0012          |
  | 0.0029        | 0.46  | 700  | 0.0009          |
  | 0.0022        | 0.52  | 800  | 0.0010          |
  | 0.0025        | 0.59  | 900  | 0.0008          |
  | 0.002         | 0.65  | 1000 | 0.0006          |
  | 0.0016        | 0.72  | 1100 | 0.0006          |
  | 0.0015        | 0.78  | 1200 | 0.0006          |
  | 0.0015        | 0.85  | 1300 | 0.0004          |
  | 0.0012        | 0.92  | 1400 | 0.0006          |
  | 0.0013        | 0.98  | 1500 | 0.0002          |
  | 0.0013        | 1.05  | 1600 | 0.0003          |
  | 0.0008        | 1.11  | 1700 | 0.0002          |
  | 0.0013        | 1.18  | 1800 | 0.0006          |
  | 0.0019        | 1.24  | 1900 | 0.0004          |
  | 0.001         | 1.31  | 2000 | 0.0002          |
  | 0.0007        | 1.37  | 2100 | 0.0003          |
  | 0.0009        | 1.44  | 2200 | 0.0003          |
  | 0.0012        | 1.5   | 2300 | 0.0002          |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0+cu117
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  