README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - pubmed-summarization
metrics:
  - rouge
model-index:
  - name: my_awesome_billsum_model
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: pubmed-summarization
          type: pubmed-summarization
          config: section
          split: test
          args: section
        metrics:
          - name: Rouge1
            type: rouge
            value: 0.1393

my_awesome_billsum_model

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

• Loss: 2.3423
• Rouge1: 0.1393
• Rouge2: 0.0556
• Rougel: 0.1172
• Rougelsum: 0.1172
• 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
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	375	2.3755	0.1375	0.0538	0.1159	0.1159	19.0
2.6739	2.0	750	2.3423	0.1393	0.0556	0.1172	0.1172	19.0

Framework versions

• Transformers 4.27.4
• Pytorch 1.13.1+cu116
• Datasets 2.11.0
• Tokenizers 0.13.2