metadata

license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
datasets:
  - multi_news
metrics:
  - rouge
model-index:
  - name: multinews_model
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: multi_news
          type: multi_news
          config: default
          split: test
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 0.1482

multinews_model

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

Loss: 2.7165
Rouge1: 0.1482
Rouge2: 0.0472
Rougel: 0.1132
Rougelsum: 0.1132
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: 10
eval_batch_size: 10
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	450	2.8616	0.1388	0.0418	0.1057	0.1056	19.0
3.2544	2.0	900	2.7991	0.1427	0.0438	0.1089	0.1089	19.0
2.999	3.0	1350	2.7693	0.1449	0.046	0.1115	0.1114	19.0
2.958	4.0	1800	2.7531	0.1466	0.0462	0.112	0.1118	19.0
2.9198	5.0	2250	2.7431	0.1466	0.0465	0.112	0.1119	19.0
2.8838	6.0	2700	2.7328	0.1474	0.0461	0.1125	0.1123	19.0
2.8774	7.0	3150	2.7270	0.1477	0.0463	0.1126	0.1124	19.0
2.8712	8.0	3600	2.7226	0.148	0.0466	0.1128	0.1127	19.0
2.854	9.0	4050	2.7197	0.1479	0.047	0.1129	0.1128	19.0
2.8541	10.0	4500	2.7188	0.1485	0.0471	0.113	0.1129	19.0
2.8541	11.0	4950	2.7168	0.1483	0.0472	0.1131	0.1131	19.0
2.8466	12.0	5400	2.7165	0.1482	0.0472	0.1132	0.1132	19.0

Framework versions

Transformers 4.33.3
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3