metadata

base_model: google/pegasus-cnn_dailymail
tags:
  - generated_from_trainer
datasets:
  - billsum
metrics:
  - rouge
model-index:
  - name: pegasuscnn-dailymail_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: 0.4804

pegasuscnn-dailymail_billsum_model

This model is a fine-tuned version of google/pegasus-cnn_dailymail on the billsum dataset. It achieves the following results on the evaluation set:

Loss: 1.6747
Rouge1: 0.4804
Rouge2: 0.2362
Rougel: 0.3218
Rougelsum: 0.3218
Gen Len: 123.3669

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: 5
eval_batch_size: 5
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.6227	1.0	198	1.9091	0.4289	0.1938	0.2945	0.2947	120.1855
1.9714	2.0	396	1.8147	0.4517	0.2093	0.3059	0.3061	120.7742
1.903	3.0	594	1.7646	0.4607	0.2207	0.3098	0.3102	121.121
1.7973	4.0	792	1.7362	0.4719	0.2264	0.3179	0.3178	122.3185
1.7868	5.0	990	1.7137	0.4779	0.2314	0.3191	0.3192	123.2379
1.7457	6.0	1188	1.6958	0.4748	0.2296	0.3171	0.317	123.2056
1.6687	7.0	1386	1.6873	0.4795	0.2352	0.3216	0.3216	123.2702
1.6751	8.0	1584	1.6806	0.4835	0.2384	0.3248	0.3245	122.8266
1.6564	9.0	1782	1.6758	0.4814	0.2359	0.3217	0.3216	123.2984
1.6333	10.0	1980	1.6747	0.4804	0.2362	0.3218	0.3218	123.3669

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1