metadata

license: apache-2.0
base_model: google/long-t5-tglobal-xl
tags:
  - generated_from_trainer
datasets:
  - tau/scrolls
metrics:
  - rouge
model-index:
  - name: longt5_xl_gov_5
    results:
      - task:
          name: Summarization
          type: summarization
        dataset:
          name: tau/scrolls gov_report
          type: tau/scrolls
          config: gov_report
          split: validation
          args: gov_report
        metrics:
          - name: Rouge1
            type: rouge
            value: 54.2522

longt5_xl_gov_5

This model is a fine-tuned version of google/long-t5-tglobal-xl on the tau/scrolls gov_report dataset. It achieves the following results on the evaluation set:

Loss: 1.4141
Rouge1: 54.2522
Rouge2: 24.7528
Rougel: 27.2444
Rougelsum: 51.5916
Gen Len: 889.25

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: 0.001
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 128
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.6209	1.0	136	1.5434	45.0062	18.1618	23.3808	41.7616	904.1996
1.418	1.99	272	1.4141	54.2522	24.7528	27.2444	51.5916	889.25
1.2626	3.0	409	1.4249	52.4332	23.708	27.2902	49.8071	878.4095
1.0992	4.0	545	1.4211	55.2041	26.5229	29.9951	52.6487	670.7047
0.9974	4.99	680	1.4569	55.9961	26.2205	29.0409	53.3109	883.0463

Framework versions

Transformers 4.34.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3