readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-large-cased-finetuned-lowR100-0-cased-DA-40
    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-lowR100-0-cased-DA-40
  
  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: 1.9481
  
  ## 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    | 1.8079          |
  | 2.0032        | 2.0   | 2    | 3.1228          |
  | 2.0032        | 3.0   | 3    | 1.9553          |
  | 1.9122        | 4.0   | 4    | 2.1789          |
  | 1.9122        | 5.0   | 5    | 1.8698          |
  | 1.9936        | 6.0   | 6    | 2.1649          |
  | 1.9936        | 7.0   | 7    | 3.3564          |
  | 1.8624        | 8.0   | 8    | 2.6206          |
  | 1.8624        | 9.0   | 9    | 2.0358          |
  | 1.8051        | 10.0  | 10   | 1.9754          |
  | 1.8051        | 11.0  | 11   | 2.5270          |
  | 2.0363        | 12.0  | 12   | 1.8028          |
  | 2.0363        | 13.0  | 13   | 2.0974          |
  | 1.7005        | 14.0  | 14   | 1.2336          |
  | 1.7005        | 15.0  | 15   | 2.0583          |
  | 1.6696        | 16.0  | 16   | 3.1515          |
  | 1.6696        | 17.0  | 17   | 2.3699          |
  | 1.5171        | 18.0  | 18   | 2.5653          |
  | 1.5171        | 19.0  | 19   | 1.6895          |
  | 1.573         | 20.0  | 20   | 1.7983          |
  | 1.573         | 21.0  | 21   | 3.0257          |
  | 1.5831        | 22.0  | 22   | 2.8107          |
  | 1.5831        | 23.0  | 23   | 1.6412          |
  | 1.6265        | 24.0  | 24   | 1.9859          |
  | 1.6265        | 25.0  | 25   | 1.7744          |
  | 1.6744        | 26.0  | 26   | 2.7989          |
  | 1.6744        | 27.0  | 27   | 1.7943          |
  | 1.5041        | 28.0  | 28   | 1.5538          |
  | 1.5041        | 29.0  | 29   | 3.9907          |
  | 1.5154        | 30.0  | 30   | 0.8862          |
  | 1.5154        | 31.0  | 31   | 1.7290          |
  | 1.5841        | 32.0  | 32   | 1.7470          |
  | 1.5841        | 33.0  | 33   | 1.9897          |
  | 1.6299        | 34.0  | 34   | 1.7316          |
  | 1.6299        | 35.0  | 35   | 1.7352          |
  | 1.6617        | 36.0  | 36   | 1.7413          |
  | 1.6617        | 37.0  | 37   | 2.7554          |
  | 1.3198        | 38.0  | 38   | 2.7426          |
  | 1.3198        | 39.0  | 39   | 1.7127          |
  | 1.6463        | 40.0  | 40   | 1.6030          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  