metadata

license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
datasets:
  - billsum
metrics:
  - rouge
model-index:
  - name: T5_summ_gen_v1
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: billsum
          type: billsum
          config: default
          split: ca_test
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 0.1986

T5_summ_gen_v1

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

Loss: 2.0950
Rouge1: 0.1986
Rouge2: 0.1044
Rougel: 0.1726
Rougelsum: 0.1727
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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	62	2.2294	0.1988	0.1023	0.1715	0.1714	19.0
No log	2.0	124	2.2038	0.1998	0.1024	0.1727	0.1725	19.0
No log	3.0	186	2.1890	0.2011	0.1049	0.1744	0.1746	19.0
No log	4.0	248	2.1767	0.2002	0.1059	0.1736	0.1737	19.0
No log	5.0	310	2.1593	0.2015	0.1064	0.1739	0.1741	19.0
No log	6.0	372	2.1522	0.2022	0.1059	0.1747	0.175	19.0
No log	7.0	434	2.1404	0.2028	0.1078	0.1746	0.1748	19.0
No log	8.0	496	2.1369	0.2015	0.1061	0.1735	0.1737	19.0
2.382	9.0	558	2.1299	0.1999	0.1053	0.1723	0.1725	19.0
2.382	10.0	620	2.1205	0.2003	0.1058	0.173	0.1729	19.0
2.382	11.0	682	2.1170	0.1998	0.105	0.1727	0.1727	19.0
2.382	12.0	744	2.1122	0.2003	0.1057	0.1734	0.1734	19.0
2.382	13.0	806	2.1084	0.1993	0.1042	0.1725	0.1726	19.0
2.382	14.0	868	2.1046	0.1988	0.1037	0.1723	0.1725	19.0
2.382	15.0	930	2.1023	0.1992	0.1047	0.1727	0.1729	19.0
2.382	16.0	992	2.1006	0.1992	0.1047	0.1727	0.1729	19.0
2.2855	17.0	1054	2.0979	0.1983	0.1034	0.1722	0.1723	19.0
2.2855	18.0	1116	2.0961	0.1988	0.1046	0.1729	0.173	19.0
2.2855	19.0	1178	2.0953	0.1986	0.1044	0.1725	0.1726	19.0
2.2855	20.0	1240	2.0950	0.1986	0.1044	0.1726	0.1727	19.0

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.5
Tokenizers 0.14.1