siddheshtv/abstractive_summarization

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abstractive_summarization

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

• —Loss: 2.0699
• —Rouge1: 0.166
• —Rouge2: 0.1297
• —Rougel: 0.1594
• —Rougelsum: 0.1593
• —Gen Len: 18.9974

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: 4
• —evalbatchsize: 4
• —seed: 42
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 8
• —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 4.41.2
• —Pytorch 2.3.0+cu121
• —Datasets 2.20.0
• —Tokenizers 0.19.1