metadata

license: apache-2.0
tags:
  - summarization
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: t5-v1_1-small-finetuned-samsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: samsum
          type: samsum
          config: samsum
          split: train
          args: samsum
        metrics:
          - name: Rouge1
            type: rouge
            value: 0.40608242084369006

t5-v1_1-small-finetuned-samsum

This model is a fine-tuned version of google/t5-v1_1-small on the samsum dataset. It achieves the following results on the evaluation set:

Loss: 2.0053
Rouge1: 0.4061
Rouge2: 0.1804
Rougel: 0.3478
Rougelsum: 0.3774

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: 5.6e-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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
3.9788	1.0	1842	2.2499	0.3743	0.1569	0.3191	0.3486
2.9091	2.0	3684	2.1052	0.3875	0.1680	0.3329	0.3607
2.6807	3.0	5526	2.0270	0.4009	0.1778	0.3439	0.3734
2.5917	4.0	7368	2.0053	0.4061	0.1804	0.3478	0.3774

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.7.1
Tokenizers 0.13.2