readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - null
  model_index:
  - name: 100perc
    results:
    - task:
        name: Causal Language Modeling
        type: text-generation
  ---
  
  <!-- 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. -->
  
  # 100perc
  
  This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4594
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 100.0
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | No log        | 1.0   | 140   | 1.8292          |
  | No log        | 2.0   | 280   | 1.7373          |
  | No log        | 3.0   | 420   | 1.6889          |
  | 2.26          | 4.0   | 560   | 1.6515          |
  | 2.26          | 5.0   | 700   | 1.6258          |
  | 2.26          | 6.0   | 840   | 1.6063          |
  | 2.26          | 7.0   | 980   | 1.5873          |
  | 1.6847        | 8.0   | 1120  | 1.5749          |
  | 1.6847        | 9.0   | 1260  | 1.5634          |
  | 1.6847        | 10.0  | 1400  | 1.5513          |
  | 1.6073        | 11.0  | 1540  | 1.5421          |
  | 1.6073        | 12.0  | 1680  | 1.5352          |
  | 1.6073        | 13.0  | 1820  | 1.5270          |
  | 1.6073        | 14.0  | 1960  | 1.5203          |
  | 1.5545        | 15.0  | 2100  | 1.5142          |
  | 1.5545        | 16.0  | 2240  | 1.5089          |
  | 1.5545        | 17.0  | 2380  | 1.5048          |
  | 1.5156        | 18.0  | 2520  | 1.5009          |
  | 1.5156        | 19.0  | 2660  | 1.4970          |
  | 1.5156        | 20.0  | 2800  | 1.4935          |
  | 1.5156        | 21.0  | 2940  | 1.4897          |
  | 1.4835        | 22.0  | 3080  | 1.4865          |
  | 1.4835        | 23.0  | 3220  | 1.4851          |
  | 1.4835        | 24.0  | 3360  | 1.4820          |
  | 1.4565        | 25.0  | 3500  | 1.4787          |
  | 1.4565        | 26.0  | 3640  | 1.4774          |
  | 1.4565        | 27.0  | 3780  | 1.4749          |
  | 1.4565        | 28.0  | 3920  | 1.4748          |
  | 1.4326        | 29.0  | 4060  | 1.4728          |
  | 1.4326        | 30.0  | 4200  | 1.4692          |
  | 1.4326        | 31.0  | 4340  | 1.4692          |
  | 1.4326        | 32.0  | 4480  | 1.4668          |
  | 1.4126        | 33.0  | 4620  | 1.4664          |
  | 1.4126        | 34.0  | 4760  | 1.4659          |
  | 1.4126        | 35.0  | 4900  | 1.4643          |
  | 1.394         | 36.0  | 5040  | 1.4622          |
  | 1.394         | 37.0  | 5180  | 1.4629          |
  | 1.394         | 38.0  | 5320  | 1.4610          |
  | 1.394         | 39.0  | 5460  | 1.4623          |
  | 1.3775        | 40.0  | 5600  | 1.4599          |
  | 1.3775        | 41.0  | 5740  | 1.4600          |
  | 1.3775        | 42.0  | 5880  | 1.4580          |
  | 1.363         | 43.0  | 6020  | 1.4584          |
  | 1.363         | 44.0  | 6160  | 1.4577          |
  | 1.363         | 45.0  | 6300  | 1.4559          |
  | 1.363         | 46.0  | 6440  | 1.4545          |
  | 1.3484        | 47.0  | 6580  | 1.4568          |
  | 1.3484        | 48.0  | 6720  | 1.4579          |
  | 1.3484        | 49.0  | 6860  | 1.4562          |
  | 1.3379        | 50.0  | 7000  | 1.4558          |
  | 1.3379        | 51.0  | 7140  | 1.4556          |
  | 1.3379        | 52.0  | 7280  | 1.4581          |
  | 1.3379        | 53.0  | 7420  | 1.4554          |
  | 1.3258        | 54.0  | 7560  | 1.4561          |
  | 1.3258        | 55.0  | 7700  | 1.4553          |
  | 1.3258        | 56.0  | 7840  | 1.4555          |
  | 1.3258        | 57.0  | 7980  | 1.4572          |
  | 1.3158        | 58.0  | 8120  | 1.4551          |
  | 1.3158        | 59.0  | 8260  | 1.4573          |
  | 1.3158        | 60.0  | 8400  | 1.4561          |
  | 1.3072        | 61.0  | 8540  | 1.4557          |
  | 1.3072        | 62.0  | 8680  | 1.4548          |
  | 1.3072        | 63.0  | 8820  | 1.4547          |
  | 1.3072        | 64.0  | 8960  | 1.4556          |
  | 1.2986        | 65.0  | 9100  | 1.4555          |
  | 1.2986        | 66.0  | 9240  | 1.4566          |
  | 1.2986        | 67.0  | 9380  | 1.4558          |
  | 1.2916        | 68.0  | 9520  | 1.4565          |
  | 1.2916        | 69.0  | 9660  | 1.4552          |
  | 1.2916        | 70.0  | 9800  | 1.4558          |
  | 1.2916        | 71.0  | 9940  | 1.4553          |
  | 1.2846        | 72.0  | 10080 | 1.4579          |
  | 1.2846        | 73.0  | 10220 | 1.4572          |
  | 1.2846        | 74.0  | 10360 | 1.4572        