metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- bills-summarization
metrics:
- rouge
model-index:
- name: ft-t5-with-dill-sum
results:
- task:
name: Summarization
type: summarization
dataset:
name: billsum
type: bills-summarization
metrics:
- name: Rouge1
type: rouge
value: 0.1441
ft-t5-with-dill-sum
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.5658
- Rouge1: 0.1441
- Rouge2: 0.0526
- Rougel: 0.1184
- Rougelsum: 0.1184
- 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 31 | 3.0881 | 0.1395 | 0.0436 | 0.1155 | 0.1154 | 19.0 |
| No log | 2.0 | 62 | 2.7574 | 0.1315 | 0.0394 | 0.109 | 0.1093 | 19.0 |
| No log | 3.0 | 93 | 2.6284 | 0.1377 | 0.0465 | 0.1138 | 0.1139 | 19.0 |
| No log | 4.0 | 124 | 2.5796 | 0.1428 | 0.0512 | 0.1177 | 0.1175 | 19.0 |
| No log | 5.0 | 155 | 2.5658 | 0.1441 | 0.0526 | 0.1184 | 0.1184 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0