--- library_name: transformers license: mit base_model: gpt2 tags: - generated_from_trainer model-index: - name: soft_real_imagenet_v0 results: [] --- # soft_real_imagenet_v0 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: 0.8118 ## 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: 16 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 1000 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:-----:|:---------------:| | 1.1003 | 1.0 | 4057 | 0.9910 | | 0.9581 | 2.0 | 8114 | 0.8864 | | 0.8894 | 3.0 | 12171 | 0.8404 | | 0.8518 | 4.0 | 16228 | 0.8199 | | 0.8356 | 5.0 | 20285 | 0.8118 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.4.1+cu121 - Datasets 2.19.1 - Tokenizers 0.20.3