--- license: mit base_model: gpt2 tags: - generated_from_trainer metrics: - accuracy model-index: - name: gmra_model_gpt2_14082023T103028 results: [] --- # gmra_model_gpt2_14082023T103028 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: 0.2685 - Accuracy: 0.9192 ## 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: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 71 | 0.6906 | 0.7742 | | No log | 1.99 | 142 | 0.4773 | 0.8286 | | No log | 2.99 | 213 | 0.3916 | 0.8708 | | No log | 4.0 | 285 | 0.3393 | 0.8849 | | No log | 5.0 | 356 | 0.3144 | 0.9007 | | No log | 5.99 | 427 | 0.2959 | 0.9112 | | No log | 6.99 | 498 | 0.2825 | 0.9165 | | 0.538 | 8.0 | 570 | 0.2803 | 0.9069 | | 0.538 | 9.0 | 641 | 0.2612 | 0.9192 | | 0.538 | 9.96 | 710 | 0.2685 | 0.9192 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3