README.md

metadata

license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
datasets:
  - billsum
metrics:
  - rouge
model-index:
  - name: my_awesome_billsum_model
    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: 0.1117

my_awesome_billsum_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: 2.9403
• Rouge1: 0.1117
• Rouge2: 0.0199
• Rougel: 0.0955
• Rougelsum: 0.0951
• 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: 8
• eval_batch_size: 8
• 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	10	4.4002	0.1333	0.0378	0.1094	0.109	19.0
No log	2.0	20	3.8225	0.1325	0.0351	0.1085	0.1081	19.0
No log	3.0	30	3.5343	0.1343	0.0361	0.1109	0.1109	19.0
No log	4.0	40	3.3920	0.1253	0.0307	0.1069	0.1067	19.0
No log	5.0	50	3.2849	0.1239	0.0275	0.1028	0.103	19.0
No log	6.0	60	3.2041	0.1227	0.0237	0.1015	0.1016	19.0
No log	7.0	70	3.1439	0.1234	0.0218	0.1022	0.1023	19.0
No log	8.0	80	3.0979	0.1286	0.026	0.1057	0.106	19.0
No log	9.0	90	3.0624	0.1298	0.0289	0.1048	0.105	19.0
No log	10.0	100	3.0351	0.1286	0.0299	0.105	0.1053	19.0
No log	11.0	110	3.0135	0.1292	0.0288	0.1066	0.1068	19.0
No log	12.0	120	2.9956	0.1148	0.0195	0.0942	0.0938	19.0
No log	13.0	130	2.9813	0.1167	0.0195	0.0943	0.0939	19.0
No log	14.0	140	2.9697	0.1129	0.0204	0.0935	0.093	19.0
No log	15.0	150	2.9606	0.1129	0.0204	0.0935	0.093	19.0
No log	16.0	160	2.9534	0.1125	0.0198	0.0934	0.0931	19.0
No log	17.0	170	2.9478	0.1117	0.0199	0.0955	0.0951	19.0
No log	18.0	180	2.9436	0.1117	0.0199	0.0955	0.0951	19.0
No log	19.0	190	2.9411	0.1117	0.0199	0.0955	0.0951	19.0
No log	20.0	200	2.9403	0.1117	0.0199	0.0955	0.0951	19.0

Framework versions

• Transformers 4.35.2
• Pytorch 2.2.0.dev20231123
• Datasets 2.15.0
• Tokenizers 0.15.0