Tristan/gpt2_summarization_reward_model

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gpt2summarizationreward_model

This model is a fine-tuned version of 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
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 4
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 64
• —totalevalbatch_size: 32
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 5

Training results

Framework versions

• —Transformers 4.26.0
• —Pytorch 1.13.1+cu117
• —Datasets 2.8.0
• —Tokenizers 0.13.2