BeyondDeepFakeDetection/ImageNet_real_moderate

1---2library_name: transformers3license: mit4base_model: gpt25tags:6- generated_from_trainer7model-index:8- name: ImageNet_real_model_v39  results: []10---11 12<!-- This model card has been generated automatically according to the information the Trainer had access to. You13should probably proofread and complete it, then remove this comment. -->14 15# ImageNet_real_model_v316 17This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.18It achieves the following results on the evaluation set:19- Loss: 0.843220 21## Model description22 23More information needed24 25## Intended uses & limitations26 27More information needed28 29## Training and evaluation data30 31More information needed32 33## Training procedure34 35### Training hyperparameters36 37The following hyperparameters were used during training:38- learning_rate: 2e-0539- train_batch_size: 840- eval_batch_size: 1641- seed: 4242- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments43- lr_scheduler_type: linear44- lr_scheduler_warmup_steps: 100045- num_epochs: 546- mixed_precision_training: Native AMP47 48### Training results49 50| Training Loss | Epoch | Step  | Validation Loss |51|:-------------:|:-----:|:-----:|:---------------:|52| 1.2001        | 1.0   | 2776  | 1.0491          |53| 1.0045        | 2.0   | 5552  | 0.9276          |54| 0.9204        | 3.0   | 8328  | 0.8754          |55| 0.8733        | 4.0   | 11104 | 0.8518          |56| 0.8653        | 5.0   | 13880 | 0.8432          |57 58 59### Framework versions60 61- Transformers 4.46.362- Pytorch 2.1.2+cu12163- Datasets 2.19.164- Tokenizers 0.20.365