|
--- |
|
license: mit |
|
base_model: facebook/bart-large-xsum |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- samsum |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: bart-large-xsum-samsum |
|
results: |
|
- task: |
|
name: Sequence-to-sequence Language Modeling |
|
type: text2text-generation |
|
dataset: |
|
name: samsum |
|
type: samsum |
|
config: samsum |
|
split: validation |
|
args: samsum |
|
metrics: |
|
- name: Rouge1 |
|
type: rouge |
|
value: 54.3742 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# bart-large-xsum-samsum |
|
|
|
This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co./facebook/bart-large-xsum) on the samsum dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4330 |
|
- Rouge1: 54.3742 |
|
- Rouge2: 29.1289 |
|
- Rougel: 44.1238 |
|
- Gen Len: 29.8973 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 3 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Gen Len | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:| |
|
| No log | 0.9989 | 460 | 0.4542 | 53.4662 | 28.4545 | 43.6636 | 29.6174 | |
|
| 0.7083 | 2.0 | 921 | 0.4415 | 53.6674 | 28.8109 | 44.0343 | 29.2665 | |
|
| 0.3748 | 2.9967 | 1380 | 0.4330 | 54.3742 | 29.1289 | 44.1238 | 29.8973 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.4 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
