metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - billsum
metrics:
  - rouge
  - bleu
model-index:
  - name: T5-small_finetuned_billsum_subset_model_bs32_lr0.0001
    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: 0.191
          - name: Bleu
            type: bleu
            value: 0.0007

T5-small_finetuned_billsum_subset_model_bs32_lr0.0001

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

Loss: 1.9700
Rouge1: 0.191
Rouge2: 0.0987
Rougel: 0.1676
Rougelsum: 0.1673
Gen Len: 19.0
Bleu: 0.0007

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: 0.0001
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	1.9769	0.1885	0.0975	0.1664	0.166	19.0	0.0008
No log	2.0	62	1.9730	0.1881	0.097	0.1643	0.1642	19.0	0.0007
No log	3.0	93	1.9753	0.1869	0.0945	0.1644	0.1642	19.0	0.0007
No log	4.0	124	1.9700	0.191	0.0987	0.1676	0.1673	19.0	0.0007

Framework versions

Transformers 4.27.4
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3