readme: ---
  license: bigscience-bloom-rail-1.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bloom-560m-finetuned-the-stack-brainfuck
    results: []
  
  widget:
  - text: "
  >+++++++++[<++++++++>-]<.>+++++++[<++++>-]<+.+++++++..+++.[-]>++++++++[<++++>-]
  <.>+++++++++++[<++++++++>-]<-.--------.+++.-[.>>+>+<<<-]>>>"
  ---
  
  <!-- 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. -->
  
  # bloom-560m-finetuned-the-stack-brainfuck
  
  This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2112
  
  ## 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: 1
  - eval_batch_size: 2
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 4
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 2
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 1.3877        | 0.1   | 200  | 1.8023          |
  | 1.2576        | 0.19  | 400  | 1.7121          |
  | 1.1452        | 0.29  | 600  | 1.5469          |
  | 1.1503        | 0.39  | 800  | 1.6261          |
  | 1.0287        | 0.48  | 1000 | 1.5097          |
  | 1.0118        | 0.58  | 1200 | 1.4398          |
  | 1.0466        | 0.67  | 1400 | 1.4267          |
  | 0.9531        | 0.77  | 1600 | 1.4130          |
  | 0.8891        | 0.87  | 1800 | 1.4026          |
  | 0.9163        | 0.96  | 2000 | 1.4003          |
  | 0.7207        | 1.06  | 2200 | 1.3758          |
  | 0.7041        | 1.16  | 2400 | 1.3364          |
  | 0.7065        | 1.25  | 2600 | 1.3095          |
  | 0.7316        | 1.35  | 2800 | 1.2959          |
  | 0.6817        | 1.45  | 3000 | 1.2682          |
  | 0.6926        | 1.54  | 3200 | 1.2567          |
  | 0.6511        | 1.64  | 3400 | 1.2416          |
  | 0.6819        | 1.73  | 3600 | 1.2263          |
  | 0.6422        | 1.83  | 3800 | 1.2206          |
  | 0.6392        | 1.93  | 4000 | 1.2112          |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0+cu117
  - Datasets 2.5.1
  - Tokenizers 0.13.0
  