--- library_name: transformers license: mit base_model: gpt2 tags: - generated_from_trainer model-index: - name: chessgpt2-small-s results: [] --- # chessgpt2-small-s This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.9942 ## 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: 0.0004 - train_batch_size: 32 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.04 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:-----:|:---------------:| | 2.2324 | 0.2560 | 1000 | 1.6718 | | 1.5685 | 0.5119 | 2000 | 1.3914 | | 1.3827 | 0.7679 | 3000 | 1.2685 | | 1.275 | 1.0238 | 4000 | 1.1896 | | 1.1969 | 1.2798 | 5000 | 1.1338 | | 1.1498 | 1.5357 | 6000 | 1.0901 | | 1.1102 | 1.7917 | 7000 | 1.0563 | | 1.0698 | 2.0476 | 8000 | 1.0300 | | 1.0221 | 2.3036 | 9000 | 1.0122 | | 1.0079 | 2.5595 | 10000 | 1.0003 | | 0.9988 | 2.8155 | 11000 | 0.9942 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.1 - Tokenizers 0.19.1