metadata
license: apache-2.0
base_model: google/long-t5-tglobal-base
tags:
- summarization
- generated_from_trainer
datasets:
- gov_report_summarization_dataset
metrics:
- rouge
model-index:
- name: long-t5-tglobal-base-finetuned-govReport-4096
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: gov_report_summarization_dataset
type: gov_report_summarization_dataset
config: document
split: validation
args: document
metrics:
- name: Rouge1
type: rouge
value: 0.0432
pipeline_tag: summarization
long-t5-tglobal-base-finetuned-govReport-4096
This model is a fine-tuned version of google/long-t5-tglobal-base on the gov_report_summarization_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 1.4052
- Rouge1: 0.0432
- Rouge2: 0.0217
- Rougel: 0.0378
- Rougelsum: 0.0408
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: 4e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 15.9484 | 0.99 | 31 | 2.7412 | 0.0382 | 0.0142 | 0.0319 | 0.0354 |
| 3.0143 | 1.98 | 62 | 1.7096 | 0.0385 | 0.0144 | 0.032 | 0.0355 |
| 2.1893 | 2.98 | 93 | 1.4976 | 0.0376 | 0.0138 | 0.0313 | 0.0347 |
| 1.6128 | 4.0 | 125 | 1.4406 | 0.041 | 0.0174 | 0.0354 | 0.0387 |
| 1.5438 | 4.99 | 156 | 1.4292 | 0.043 | 0.0203 | 0.0368 | 0.0408 |
| 1.5015 | 5.98 | 187 | 1.4220 | 0.0427 | 0.0205 | 0.0367 | 0.0405 |
| 1.4723 | 6.98 | 218 | 1.4071 | 0.0431 | 0.0215 | 0.0376 | 0.0408 |
| 1.4707 | 8.0 | 250 | 1.4089 | 0.0427 | 0.0212 | 0.0373 | 0.0405 |
| 1.4447 | 8.99 | 281 | 1.4046 | 0.0431 | 0.0216 | 0.0379 | 0.0408 |
| 1.4884 | 9.92 | 310 | 1.4052 | 0.0432 | 0.0217 | 0.0378 | 0.0408 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1