gpt2-summarization_reward_model

Tristan/gpt2-summarization_reward_model

gpt2-summarization_reward_model is a machine learning model from Tristan. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

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Public

Updated Jan 26, 2023

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5.1 GB

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Hugging Face

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At a glance

License: mit
Access: Public
Created: Jan 23, 2023
Updated: Jan 26, 2023
SHA: dfa3edb3

Model card

From the Hugging Face model README

gpt2-summarization_reward_model

This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7473
Accuracy: 0.6006

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: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 16
total_train_batch_size: 64
total_eval_batch_size: 64
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
0.6421	1.0	1451	0.6815	0.6036
0.5893	2.0	2902	0.6764	0.6048
0.5488	3.0	4353	0.7074	0.6012
0.5187	4.0	5804	0.7254	0.6009
0.5034	5.0	7255	0.7473	0.6006

Framework versions

Transformers 4.26.0
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.2

License: mit
Created: Jan 23, 2023
Updated: Jan 26, 2023