readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: gpt-m
    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. -->
  
  # gpt-m
  
  This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0161
  
  ## 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: 0.0002
  - 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
  - training_steps: 10000
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 0.5632        | 0.06  | 500   | 0.0369          |
  | 0.0328        | 0.11  | 1000  | 0.0270          |
  | 0.0825        | 0.17  | 1500  | 0.0268          |
  | 0.0265        | 0.22  | 2000  | 0.0259          |
  | 0.2434        | 0.28  | 2500  | 0.6319          |
  | 2.0273        | 0.33  | 3000  | 0.0257          |
  | 0.0236        | 0.39  | 3500  | 0.0227          |
  | 0.024         | 0.44  | 4000  | 0.0226          |
  | 0.0211        | 0.5   | 4500  | 0.0207          |
  | 0.0223        | 0.56  | 5000  | 0.0200          |
  | 0.0193        | 0.61  | 5500  | 0.0189          |
  | 0.0197        | 0.67  | 6000  | 0.0184          |
  | 0.0187        | 0.72  | 6500  | 0.0183          |
  | 0.0193        | 0.78  | 7000  | 0.0183          |
  | 0.0191        | 0.83  | 7500  | 0.0175          |
  | 0.0194        | 0.89  | 8000  | 0.0170          |
  | 0.0172        | 0.94  | 8500  | 0.0167          |
  | 0.0166        | 1.0   | 9000  | 0.0165          |
  | 0.0153        | 1.06  | 9500  | 0.0162          |
  | 0.0158        | 1.11  | 10000 | 0.0161          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  