metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: summarizer
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: multi_news
type: multi_news
config: default
split: test
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.1434
summarizer
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: 2.7745
- Rouge1: 0.1434
- Rouge2: 0.0448
- Rougel: 0.1097
- Rougelsum: 0.1097
- Gen Len: 18.9968
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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 352 | 2.8572 | 0.1386 | 0.0423 | 0.106 | 0.106 | 18.9968 |
| 3.2016 | 2.0 | 704 | 2.8029 | 0.1415 | 0.0435 | 0.108 | 0.108 | 18.9966 |
| 3.0361 | 3.0 | 1056 | 2.7814 | 0.143 | 0.0446 | 0.1093 | 0.1093 | 18.9968 |
| 3.0361 | 4.0 | 1408 | 2.7745 | 0.1434 | 0.0448 | 0.1097 | 0.1097 | 18.9968 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2