readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: codeparrot-ds-500sample-gpt-neo-2ep
    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. -->
  
  # codeparrot-ds-500sample-gpt-neo-2ep
  
  This model is a fine-tuned version of [EleutherAI/gpt-neo-125M](https://huggingface.co/EleutherAI/gpt-neo-125M) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.5483
  
  ## 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: 0.0005
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 256
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 2
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 4.5248        | 0.19  | 1000  | 2.9757          |
  | 2.5422        | 0.37  | 2000  | 2.4397          |
  | 2.1642        | 0.56  | 3000  | 2.1880          |
  | 1.9135        | 0.74  | 4000  | 1.9884          |
  | 1.7236        | 0.93  | 5000  | 1.8470          |
  | 1.5459        | 1.11  | 6000  | 1.7501          |
  | 1.4363        | 1.3   | 7000  | 1.6761          |
  | 1.3639        | 1.49  | 8000  | 1.6105          |
  | 1.3046        | 1.67  | 9000  | 1.5667          |
  | 1.273         | 1.86  | 10000 | 1.5483          |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  