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: 0.1432
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: 2.5046
- Rouge1: 0.1432
- Rouge2: 0.0554
- Rougel: 0.1209
- Rougelsum: 0.1206
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 62 | 2.7936 | 0.1313 | 0.0438 | 0.1113 | 0.1112 | 19.0 |
| No log | 2.0 | 124 | 2.5853 | 0.1386 | 0.0512 | 0.1176 | 0.1175 | 19.0 |
| No log | 3.0 | 186 | 2.5217 | 0.1415 | 0.0533 | 0.1194 | 0.1193 | 19.0 |
| No log | 4.0 | 248 | 2.5046 | 0.1432 | 0.0554 | 0.1209 | 0.1206 | 19.0 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1