metadata

license: apache-2.0
tags:
  - summarization
  - generated_from_trainer
datasets:
  - snli
metrics:
  - rouge
model-index:
  - name: t5-small-finetuned-contradiction
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: snli
          type: snli
          args: plain_text
        metrics:
          - name: Rouge1
            type: rouge
            value: 34.3638

t5-small-finetuned-contradiction

This model is a fine-tuned version of domenicrosati/t5-small-finetuned-contradiction on the snli dataset. It achieves the following results on the evaluation set:

Loss: 2.1269
Rouge1: 34.3638
Rouge2: 14.7916
Rougel: 32.6308
Rougelsum: 32.6288

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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
2.1984	1.0	2863	2.1556	34.4429	14.6791	32.5812	32.5896
2.2085	2.0	5726	2.1390	34.3719	14.731	32.5979	32.5949
2.188	3.0	8589	2.1302	34.4276	14.7191	32.62	32.6132
2.1768	4.0	11452	2.1269	34.4408	14.8235	32.7067	32.7065

Framework versions

Transformers 4.18.0
Pytorch 1.11.0+cu102
Datasets 2.1.0
Tokenizers 0.12.1