metadata
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: bart-base-facebook
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
split: train
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.7146
bart-base-facebook
This model is a fine-tuned version of facebook/bart-base on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.1877
- Rouge1: 0.7146
- Rouge2: 0.3305
- Rougel: 0.2988
- Rougelsum: 0.6822
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: 5.6e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.505 | 1.0 | 1359 | 2.1048 | 0.6788 | 0.3022 | 0.2843 | 0.6497 |
| 2.0216 | 2.0 | 2718 | 2.1010 | 0.7022 | 0.3182 | 0.2974 | 0.672 |
| 1.7088 | 3.0 | 4077 | 2.1228 | 0.7048 | 0.3214 | 0.2968 | 0.6722 |
| 1.4778 | 4.0 | 5436 | 2.1655 | 0.7117 | 0.325 | 0.2984 | 0.6786 |
| 1.3161 | 5.0 | 6795 | 2.1877 | 0.7146 | 0.3305 | 0.2988 | 0.6822 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.2
- Tokenizers 0.12.1