readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-large-cased-finetuned-lowR100-3-cased-DA-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. -->
  
  # bert-large-cased-finetuned-lowR100-3-cased-DA-20
  
  This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.5250
  
  ## 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: 30
  - eval_batch_size: 30
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 40.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | No log        | 1.0   | 1    | 6.8611          |
  | 6.5268        | 2.0   | 2    | 8.5069          |
  | 6.5268        | 3.0   | 3    | 6.4383          |
  | 6.3552        | 4.0   | 4    | 5.2540          |
  | 6.3552        | 5.0   | 5    | 6.2490          |
  | 5.5713        | 6.0   | 6    | 5.8587          |
  | 5.5713        | 7.0   | 7    | 5.6369          |
  | 5.0248        | 8.0   | 8    | 5.1667          |
  | 5.0248        | 9.0   | 9    | 4.8407          |
  | 4.364         | 10.0  | 10   | 5.0590          |
  | 4.364         | 11.0  | 11   | 4.8647          |
  | 3.6607        | 12.0  | 12   | 3.3072          |
  | 3.6607        | 13.0  | 13   | 3.4963          |
  | 3.3901        | 14.0  | 14   | 4.0039          |
  | 3.3901        | 15.0  | 15   | 3.5993          |
  | 3.1245        | 16.0  | 16   | 2.2179          |
  | 3.1245        | 17.0  | 17   | 1.6414          |
  | 3.1906        | 18.0  | 18   | 3.1965          |
  | 3.1906        | 19.0  | 19   | 3.1463          |
  | 2.7243        | 20.0  | 20   | 3.1866          |
  | 2.7243        | 21.0  | 21   | 1.0648          |
  | 2.944         | 22.0  | 22   | 3.2413          |
  | 2.944         | 23.0  | 23   | 3.1838          |
  | 2.7114        | 24.0  | 24   | 3.8036          |
  | 2.7114        | 25.0  | 25   | 2.2897          |
  | 2.4176        | 26.0  | 26   | 3.6953          |
  | 2.4176        | 27.0  | 27   | 3.3176          |
  | 2.4277        | 28.0  | 28   | 2.9940          |
  | 2.4277        | 29.0  | 29   | 3.0186          |
  | 2.4099        | 30.0  | 30   | 3.0385          |
  | 2.4099        | 31.0  | 31   | 1.9323          |
  | 2.2141        | 32.0  | 32   | 2.2952          |
  | 2.2141        | 33.0  | 33   | 3.5302          |
  | 2.4007        | 34.0  | 34   | 3.7787          |
  | 2.4007        | 35.0  | 35   | 3.3718          |
  | 2.2619        | 36.0  | 36   | 2.2895          |
  | 2.2619        | 37.0  | 37   | 2.7433          |
  | 2.4834        | 38.0  | 38   | 3.5129          |
  | 2.4834        | 39.0  | 39   | 1.7792          |
  | 2.122         | 40.0  | 40   | 2.5250          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  