readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: BERiT_14500
    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. -->
  
  # BERiT_14500
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 8.0316
  
  ## 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: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 8.3825        | 0.19  | 500  | 8.3006          |
  | 8.2426        | 0.39  | 1000 | 8.2751          |
  | 8.1622        | 0.58  | 1500 | 8.2504          |
  | 8.1673        | 0.77  | 2000 | 8.1935          |
  | 8.1597        | 0.97  | 2500 | 8.1928          |
  | 8.0644        | 1.16  | 3000 | 8.1111          |
  | 8.0724        | 1.36  | 3500 | 8.0820          |
  | 8.0654        | 1.55  | 4000 | 8.0655          |
  | 8.0649        | 1.74  | 4500 | 8.0896          |
  | 8.051         | 1.94  | 5000 | 8.0838          |
  | 8.0003        | 2.13  | 5500 | 8.0989          |
  | 7.9795        | 2.32  | 6000 | 8.0729          |
  | 7.9984        | 2.52  | 6500 | 8.0566          |
  | 7.9935        | 2.71  | 7000 | 8.0757          |
  | 7.9652        | 2.9   | 7500 | 8.0316          |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  