akash2212/text-summarization-evaluation-model

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text-summarization-evaluation-model

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

• —Loss: 2.4100
• —Rouge1: 0.1909
• —Rouge2: 0.0934
• —Rougel: 0.1617
• —Rougelsum: 0.1619
• —Gen Len: 19.0

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: 16
• —evalbatchsize: 16
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 4
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.35.2
• —Pytorch 2.1.0+cu121
• —Datasets 2.15.0
• —Tokenizers 0.15.0