PFcoding/medicare-gpt2-test1

1---2license: mit3tags:4- generated_from_trainer5datasets:6- pubmed-summarization7model-index:8- name: medicare-gpt2-test19  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# medicare-gpt2-test116 17This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the pubmed-summarization dataset.18 19## Model description20 21More information needed22 23## Intended uses & limitations24 25More information needed26 27## Training and evaluation data28 29More information needed30 31## Training procedure32 33### Training hyperparameters34 35The following hyperparameters were used during training:36- learning_rate: 0.000537- train_batch_size: 3238- eval_batch_size: 3239- seed: 4240- gradient_accumulation_steps: 841- total_train_batch_size: 25642- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0843- lr_scheduler_type: cosine44- lr_scheduler_warmup_steps: 100045- num_epochs: 146- mixed_precision_training: Native AMP47 48### Training results49 50 51 52### Framework versions53 54- Transformers 4.28.055- Pytorch 2.0.1+cu11856- Datasets 2.12.057- Tokenizers 0.13.358