pytorch vision-encoder-decoder transformers generated_from_trainer model-index
---
tags:
- generated_from_trainer
model-index:
- name: ViT-BERT-Chess-V4
  results: []
---

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# 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
