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gpt-j-claim-generator

This model is a fine-tuned version of EleutherAI/gpt-j-6b on the anli dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0232
  • Rouge1: 0.8914
  • Rouge2: 0.8240
  • Rougel: 0.8863
  • Rougelsum: 0.8864

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: 1e-05
  • train_batch_size: 12
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 3
  • total_train_batch_size: 36
  • total_eval_batch_size: 3
  • optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
0.013 1.79 5000 0.0200 0.8921 0.8194 0.8859 0.8860
0.0085 3.58 10000 0.0232 0.8914 0.8240 0.8863 0.8864

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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Dataset used to train Tverous/gpt-j-claim-generator

Evaluation results