readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: ViT-BERT-Chess-V4
    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. -->
  
  # ViT-BERT-Chess-V4
  
  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.3213
  
  ## 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: 2e-05
  - train_batch_size: 8
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 3.705         | 1.0   | 3895  | 3.5686          |
  | 3.5139        | 2.0   | 7790  | 3.4288          |
  | 3.4156        | 3.0   | 11685 | 3.3663          |
  | 3.3661        | 4.0   | 15580 | 3.3331          |
  | 3.3352        | 5.0   | 19475 | 3.3213          |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu116
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  