|
--- |
|
license: apache-2.0 |
|
base_model: facebook/bart-base |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- samsum |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: samsum_139_bart-base |
|
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: 0.4834 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# samsum_139_bart-base |
|
|
|
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the samsum dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5331 |
|
- Rouge1: 0.4834 |
|
- Rouge2: 0.2527 |
|
- Rougel: 0.4093 |
|
- Rougelsum: 0.4092 |
|
- Gen Len: 18.3215 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 16 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
|
| 0.5323 | 4.34 | 500 | 0.5449 | 0.4788 | 0.2457 | 0.4002 | 0.4004 | 18.7653 | |
|
| 0.4101 | 8.69 | 1000 | 0.5331 | 0.4834 | 0.2527 | 0.4093 | 0.4092 | 18.3215 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.2 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
