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T5_Model

This model is a fine-tuned version of t5-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7795
  • Rouge1: 0.2473
  • Rouge2: 0.1174
  • Rougel: 0.2041
  • Rougelsum: 0.2042
  • Gen Len: 18.9999

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: 3e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: tpu
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 8
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.0058 1.0 35890 1.8209 0.247 0.1174 0.2039 0.2039 18.9992
1.9949 2.0 71780 1.8004 0.2469 0.117 0.2036 0.2036 18.9995
1.948 3.0 107670 1.7938 0.2477 0.1176 0.2047 0.2047 18.9999
1.9459 4.0 143560 1.7884 0.2478 0.1182 0.2049 0.2049 18.9999
1.924 5.0 179450 1.7844 0.2477 0.1179 0.2045 0.2046 18.9996
1.9301 6.0 215340 1.7824 0.2477 0.1179 0.2044 0.2044 18.9999
1.9284 7.0 251230 1.7808 0.2474 0.1177 0.2044 0.2045 18.9999
1.9217 8.0 287120 1.7795 0.2473 0.1174 0.2041 0.2042 18.9999

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.0.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Base model

google-t5/t5-small
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Dataset used to train dheeraj-kj/T5_Model

Evaluation results