--- license: mit tags: - generated_from_trainer metrics: - accuracy model-index: - name: gpt2_summarization_reward_model results: [] --- # gpt2_summarization_reward_model This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7376 - Accuracy: 0.6020 ## 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: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.6521 | 1.0 | 1451 | 0.6670 | 0.6037 | | 0.6101 | 2.0 | 2902 | 0.6763 | 0.6022 | | 0.5772 | 3.0 | 4353 | 0.7034 | 0.6026 | | 0.5503 | 4.0 | 5804 | 0.7215 | 0.6024 | | 0.5347 | 5.0 | 7255 | 0.7376 | 0.6020 | ### Framework versions - Transformers 4.26.0 - Pytorch 1.13.1+cu117 - Datasets 2.8.0 - Tokenizers 0.13.2