|
--- |
|
license: mit |
|
base_model: philschmid/bart-large-cnn-samsum |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: bart-large-cnn-samsum-dc |
|
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-large-cnn-samsum-dc |
|
|
|
This model is a fine-tuned version of [philschmid/bart-large-cnn-samsum](https://huggingface.co/philschmid/bart-large-cnn-samsum) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.7404 |
|
- Rouge1: 32.5028 |
|
- Rouge2: 13.6008 |
|
- Rougel: 23.6102 |
|
- Rougelsum: 25.0002 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
|
| 1.9176 | 1.0 | 2676 | 1.7297 | 31.7614 | 13.0816 | 22.9243 | 24.6866 | |
|
| 1.4492 | 2.0 | 5352 | 1.5775 | 32.2161 | 13.4673 | 23.7824 | 25.0772 | |
|
| 1.1499 | 3.0 | 8028 | 1.5778 | 33.1269 | 14.0686 | 24.2058 | 25.39 | |
|
| 0.8947 | 4.0 | 10704 | 1.6344 | 32.9016 | 13.9786 | 24.1741 | 25.5371 | |
|
| 0.6905 | 5.0 | 13380 | 1.7404 | 32.5028 | 13.6008 | 23.6102 | 25.0002 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
