|
|
--- |
|
|
library_name: transformers |
|
|
license: apache-2.0 |
|
|
base_model: facebook/bart-large |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: bart-summarizer |
|
|
results: [] |
|
|
--- |
|
|
|
|
|
<!-- 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-summarizer |
|
|
|
|
|
This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 2.1898 |
|
|
- Rouge1: 51.7683 |
|
|
- Rouge2: 36.3956 |
|
|
- Rougel: 45.7626 |
|
|
- Rougelsum: 45.7512 |
|
|
- Bert F1: 89.7697 |
|
|
|
|
|
## 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: 4 |
|
|
- eval_batch_size: 4 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 4 |
|
|
- total_train_batch_size: 16 |
|
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: cosine |
|
|
- lr_scheduler_warmup_ratio: 0.1 |
|
|
- num_epochs: 5 |
|
|
- mixed_precision_training: Native AMP |
|
|
- label_smoothing_factor: 0.1 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bert F1 | |
|
|
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
|
| 2.48 | 1.0 | 766 | 2.3197 | 46.084 | 31.1672 | 40.7261 | 40.733 | 88.58 | |
|
|
| 2.203 | 2.0 | 1532 | 2.2230 | 49.9815 | 34.8577 | 44.2515 | 44.2457 | 89.3509 | |
|
|
| 2.1447 | 3.0 | 2298 | 2.1980 | 50.7333 | 35.3908 | 44.6146 | 44.6091 | 89.4589 | |
|
|
| 2.0614 | 4.0 | 3064 | 2.1907 | 51.6468 | 36.4567 | 45.7548 | 45.7343 | 89.7909 | |
|
|
| 2.0515 | 4.9941 | 3825 | 2.1898 | 51.7683 | 36.3956 | 45.7626 | 45.7512 | 89.7697 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.47.0 |
|
|
- Pytorch 2.5.1+cu121 |
|
|
- Datasets 3.3.1 |
|
|
- Tokenizers 0.21.0 |
|
|
|
