---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: chess_gpt
  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. -->

# chess_gpt

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: 2.4539

## 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: 0.0003
- train_batch_size: 96
- eval_batch_size: 96
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.9) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 4.8573        | 0.0942 | 500   | 4.6881          |
| 4.0115        | 0.1884 | 1000  | 3.8051          |
| 3.6439        | 0.2826 | 1500  | 3.4294          |
| 3.4261        | 0.3769 | 2000  | 3.2262          |
| 3.2929        | 0.4711 | 2500  | 3.0936          |
| 3.1784        | 0.5653 | 3000  | 2.9891          |
| 3.1042        | 0.6595 | 3500  | 2.9109          |
| 3.0348        | 0.7537 | 4000  | 2.8448          |
| 2.9826        | 0.8479 | 4500  | 2.7931          |
| 2.9282        | 0.9422 | 5000  | 2.7484          |
| 2.8859        | 1.0364 | 5500  | 2.7090          |
| 2.8502        | 1.1306 | 6000  | 2.6747          |
| 2.8225        | 1.2248 | 6500  | 2.6463          |
| 2.7970        | 1.3190 | 7000  | 2.6216          |
| 2.7716        | 1.4132 | 7500  | 2.5987          |
| 2.7500        | 1.5074 | 8000  | 2.5777          |
| 2.7315        | 1.6017 | 8500  | 2.5614          |
| 2.7069        | 1.6959 | 9000  | 2.5424          |
| 2.6970        | 1.7901 | 9500  | 2.5273          |
| 2.6773        | 1.8843 | 10000 | 2.5158          |
| 2.6660        | 1.9785 | 10500 | 2.5039          |
| 2.6524        | 2.0727 | 11000 | 2.4941          |
| 2.6415        | 2.1669 | 11500 | 2.4847          |
| 2.6324        | 2.2612 | 12000 | 2.4775          |
| 2.6318        | 2.3554 | 12500 | 2.4720          |
| 2.6227        | 2.4496 | 13000 | 2.4655          |
| 2.6203        | 2.5438 | 13500 | 2.4612          |
| 2.6169        | 2.6380 | 14000 | 2.4581          |
| 2.6174        | 2.7322 | 14500 | 2.4562          |
| 2.6103        | 2.8265 | 15000 | 2.4544          |
| 2.6106        | 2.9207 | 15500 | 2.4540          |
| 2.6079        | 3.0    | 15921 | 2.4539          |


### Framework versions

- Transformers 5.9.0
- Pytorch 2.12.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2