metadata
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned-billsum-ca_test
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: billsum
type: billsum
args: default
metrics:
- name: Rouge1
type: rouge
value: 52.2582
t5-small-finetuned-billsum-ca_test
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.5234
- Rouge1: 52.2582
- Rouge2: 34.8162
- Rougel: 50.5491
- Rougelsum: 50.6121
- Gen Len: 18.996
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: 2
- eval_batch_size: 2
- 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 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 495 | 1.8113 | 58.4024 | 41.7432 | 56.9521 | 57.0516 | 18.9597 |
| 2.709 | 2.0 | 990 | 1.6230 | 47.7769 | 32.1777 | 46.0344 | 46.046 | 18.996 |
| 1.9323 | 3.0 | 1485 | 1.5459 | 51.2371 | 33.8242 | 49.4532 | 49.5038 | 18.996 |
| 1.7842 | 4.0 | 1980 | 1.5234 | 52.2582 | 34.8162 | 50.5491 | 50.6121 | 18.996 |
Framework versions
- Transformers 4.12.2
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3