metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: text-summarization-evaluation-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: 0.1909
text-summarization-evaluation-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: 2.4100
- Rouge1: 0.1909
- Rouge2: 0.0934
- Rougel: 0.1617
- Rougelsum: 0.1619
- 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: 16
- eval_batch_size: 16
- 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 | 62 | 2.4775 | 0.1556 | 0.0622 | 0.1297 | 0.1301 | 19.0 |
| No log | 2.0 | 124 | 2.4374 | 0.1822 | 0.0868 | 0.1534 | 0.1537 | 19.0 |
| No log | 3.0 | 186 | 2.4164 | 0.1888 | 0.0922 | 0.16 | 0.1602 | 19.0 |
| No log | 4.0 | 248 | 2.4100 | 0.1909 | 0.0934 | 0.1617 | 0.1619 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0