metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: my_awesome_billsum_model
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: 0.1936
my_awesome_billsum_model
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.4120
- Rouge1: 0.1936
- Rouge2: 0.0953
- Rougel: 0.1634
- Rougelsum: 0.1639
- Gen Len: 19.0
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: 6
- eval_batch_size: 6
- 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 | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 165 | 2.5849 | 0.1385 | 0.0467 | 0.1135 | 0.1135 | 19.0 |
| No log | 2.0 | 330 | 2.4695 | 0.1694 | 0.0731 | 0.1422 | 0.1424 | 19.0 |
| No log | 3.0 | 495 | 2.4234 | 0.1926 | 0.0938 | 0.1625 | 0.1627 | 19.0 |
| 2.8423 | 4.0 | 660 | 2.4120 | 0.1936 | 0.0953 | 0.1634 | 0.1639 | 19.0 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3