metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: results
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: multi_news
type: multi_news
config: default
split: validation
args: default
metrics:
- name: Rouge1
type: rouge
value: 37.35992631839289
results
This model is a fine-tuned version of t5-small on the multi_news dataset. It achieves the following results on the evaluation set:
- Loss: 2.9028
- Rouge1: 37.3599
- Rouge2: 12.1820
- Rougel: 21.4068
- Rougelsum: 21.3827
- Gen Len: 141.366
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 313 | 3.0888 | 33.8257 | 10.0913 | 19.3859 | 19.3966 | 131.264 |
| 3.487 | 2.0 | 626 | 3.0216 | 36.0141 | 11.1691 | 20.4601 | 20.4538 | 138.12 |
| 3.487 | 3.0 | 939 | 2.9906 | 36.2470 | 11.3578 | 20.6635 | 20.6692 | 138.632 |
| 3.2354 | 4.0 | 1252 | 2.9727 | 36.7252 | 11.5422 | 20.9492 | 20.9458 | 139.433 |
| 3.1863 | 5.0 | 1565 | 2.9586 | 36.6970 | 11.6533 | 20.9281 | 20.9236 | 140.189 |
| 3.1863 | 6.0 | 1878 | 2.9511 | 36.8584 | 11.7427 | 21.1395 | 21.1377 | 140.747 |
| 3.1624 | 7.0 | 2191 | 2.9441 | 36.9490 | 11.8362 | 21.2388 | 21.2508 | 140.994 |
| 3.1462 | 8.0 | 2504 | 2.9406 | 37.0855 | 11.8388 | 21.2447 | 21.2583 | 141.331 |
| 3.1462 | 9.0 | 2817 | 2.9383 | 37.0757 | 11.8588 | 21.2306 | 21.2472 | 140.901 |
| 3.1409 | 10.0 | 3130 | 2.9376 | 37.1450 | 11.9259 | 21.3013 | 21.3147 | 141.081 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1