metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: t5
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: 0.1248
t5
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.0846
- Rouge1: 0.1248
- Rouge2: 0.0719
- Rougel: 0.1096
- Rougelsum: 0.1097
- 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 248 | 2.3488 | 0.0936 | 0.0361 | 0.0801 | 0.0799 | 19.0 |
| No log | 2.0 | 496 | 2.2214 | 0.1098 | 0.0519 | 0.0953 | 0.0953 | 19.0 |
| 2.8859 | 3.0 | 744 | 2.1603 | 0.1243 | 0.0682 | 0.1082 | 0.1081 | 19.0 |
| 2.8859 | 4.0 | 992 | 2.1276 | 0.1255 | 0.0717 | 0.1098 | 0.1099 | 19.0 |
| 2.3699 | 5.0 | 1240 | 2.1063 | 0.1252 | 0.0715 | 0.1101 | 0.1102 | 19.0 |
| 2.3699 | 6.0 | 1488 | 2.0908 | 0.1254 | 0.0723 | 0.1099 | 0.1101 | 19.0 |
| 2.2841 | 7.0 | 1736 | 2.0862 | 0.1247 | 0.0718 | 0.1093 | 0.1094 | 19.0 |
| 2.2841 | 8.0 | 1984 | 2.0846 | 0.1248 | 0.0719 | 0.1096 | 0.1097 | 19.0 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0