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t5-base-summarization

This model is a fine-tuned version of t5-base on the cnn_dailymail 3.0.0 dataset.

Model description

More information needed

Intended uses & limitations

This is a work in progress. Please don't use these weights. :)

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0001
  • train_batch_size: 1
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: IPU
  • gradient_accumulation_steps: 256
  • total_train_batch_size: 512
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.15
  • num_epochs: 5.0
  • training precision: Mixed Precision

Training results

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.10.0+cpu
  • Datasets 2.1.0
  • Tokenizers 0.12.1
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Dataset used to train jimypbr/t5-base-test