readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: enlm-roberta-final
    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. -->
  
  # enlm-roberta-final
  
  This model is a fine-tuned version of [manirai91/enlm-roberta](https://huggingface.co/manirai91/enlm-roberta) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4187
  
  ## 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: 6e-06
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 4
  - gradient_accumulation_steps: 128
  - total_train_batch_size: 8192
  - total_eval_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
  - lr_scheduler_type: polynomial
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 1.5245        | 0.34  | 160  | 1.4187          |
  | 1.5245        | 0.69  | 320  | 1.4183          |
  | 1.5259        | 1.03  | 480  | 1.4177          |
  | 1.5265        | 1.37  | 640  | 1.4185          |
  | 1.5245        | 1.72  | 800  | 1.4190          |
  | 1.5241        | 2.06  | 960  | 1.4172          |
  | 1.5227        | 2.4   | 1120 | 1.4165          |
  | 1.5226        | 2.75  | 1280 | 1.4152          |
  | 1.522         | 3.09  | 1440 | 1.4190          |
  | 1.5243        | 3.43  | 1600 | 1.4177          |
  | 1.5213        | 3.78  | 1760 | 1.4134          |
  | 1.524         | 4.12  | 1920 | 1.4140          |
  | 1.5223        | 4.46  | 2080 | 1.4173          |
  | 1.5236        | 4.81  | 2240 | 1.4121          |
  | 1.5239        | 5.15  | 2400 | 1.4186          |
  | 1.5203        | 5.49  | 2560 | 1.4154          |
  | 1.522         | 5.84  | 2720 | 1.4162          |
  | 1.5209        | 6.18  | 2880 | 1.4154          |
  | 1.5196        | 6.52  | 3040 | 1.4153          |
  | 1.5209        | 6.87  | 3200 | 1.4122          |
  | 1.5202        | 7.21  | 3360 | 1.4146          |
  | 1.5192        | 7.55  | 3520 | 1.4141          |
  | 1.5215        | 7.9   | 3680 | 1.4123          |
  | 1.5228        | 8.24  | 3840 | 1.4147          |
  | 1.5222        | 8.58  | 4000 | 1.4144          |
  | 1.5201        | 8.93  | 4160 | 1.4173          |
  | 1.523         | 9.27  | 4320 | 1.4171          |
  | 1.5212        | 9.61  | 4480 | 1.4149          |
  | 1.522         | 9.96  | 4640 | 1.4187          |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  