metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - billsum
metrics:
  - rouge
  - bleu
model-index:
  - name: T5-small_finetuned_billsum_subset_model_bs32_lr2e-05
    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: 0.1887
          - name: Bleu
            type: bleu
            value: 0.0008

T5-small_finetuned_billsum_subset_model_bs32_lr2e-05

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

Loss: 1.9763
Rouge1: 0.1887
Rouge2: 0.0967
Rougel: 0.1659
Rougelsum: 0.1657
Gen Len: 19.0
Bleu: 0.0008

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: 32
eval_batch_size: 32
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	Gen Len	Bleu
No log	1.0	31	1.9837	0.1873	0.0945	0.1635	0.1633	19.0	0.0007
No log	2.0	62	1.9812	0.1884	0.0955	0.1652	0.1648	19.0	0.0007
No log	3.0	93	1.9785	0.1866	0.0936	0.1636	0.1634	19.0	0.0007
No log	4.0	124	1.9763	0.1887	0.0967	0.1659	0.1657	19.0	0.0008

Framework versions

Transformers 4.27.4
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3