readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-large-uncased-finetuned-lowR100-4-uncased-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-uncased-finetuned-lowR100-4-uncased-DA-20
  
  This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.2624
  
  ## 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    | 5.4063          |
  | 5.9654        | 2.0   | 2    | 6.1913          |
  | 5.9654        | 3.0   | 3    | 5.8608          |
  | 5.5864        | 4.0   | 4    | 4.4613          |
  | 5.5864        | 5.0   | 5    | 5.0257          |
  | 5.1093        | 6.0   | 6    | 4.7405          |
  | 5.1093        | 7.0   | 7    | 4.7516          |
  | 4.3965        | 8.0   | 8    | 3.1646          |
  | 4.3965        | 9.0   | 9    | 3.7378          |
  | 3.7825        | 10.0  | 10   | 2.0073          |
  | 3.7825        | 11.0  | 11   | 5.5725          |
  | 3.009         | 12.0  | 12   | 3.0077          |
  | 3.009         | 13.0  | 13   | 2.6288          |
  | 2.7427        | 14.0  | 14   | 2.8630          |
  | 2.7427        | 15.0  | 15   | 2.3270          |
  | 2.4122        | 16.0  | 16   | 3.3092          |
  | 2.4122        | 17.0  | 17   | 2.7499          |
  | 2.3707        | 18.0  | 18   | 3.2892          |
  | 2.3707        | 19.0  | 19   | 2.9385          |
  | 2.6243        | 20.0  | 20   | 1.5626          |
  | 2.6243        | 21.0  | 21   | 1.0104          |
  | 2.1606        | 22.0  | 22   | 3.3464          |
  | 2.1606        | 23.0  | 23   | 3.9334          |
  | 2.1419        | 24.0  | 24   | 1.7512          |
  | 2.1419        | 25.0  | 25   | 2.5855          |
  | 2.2265        | 26.0  | 26   | 2.2896          |
  | 2.2265        | 27.0  | 27   | 2.3118          |
  | 2.2539        | 28.0  | 28   | 2.9997          |
  | 2.2539        | 29.0  | 29   | 3.0682          |
  | 2.3866        | 30.0  | 30   | 3.3435          |
  | 2.3866        | 31.0  | 31   | 3.5848          |
  | 2.1788        | 32.0  | 32   | 2.4658          |
  | 2.1788        | 33.0  | 33   | 2.4060          |
  | 2.0932        | 34.0  | 34   | 2.8497          |
  | 2.0932        | 35.0  | 35   | 3.8500          |
  | 1.9799        | 36.0  | 36   | 1.9458          |
  | 1.9799        | 37.0  | 37   | 2.4557          |
  | 2.0164        | 38.0  | 38   | 3.3370          |
  | 2.0164        | 39.0  | 39   | 3.6850          |
  | 2.1732        | 40.0  | 40   | 1.7986          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  