|
--- |
|
license: mit |
|
base_model: facebook/bart-large-cnn |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: bart-large-cnn-finetuned-scope1-summarization |
|
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-finetuned-scope1-summarization |
|
|
|
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0612 |
|
- Rouge1: 55.9874 |
|
- Rouge2: 41.0458 |
|
- Rougel: 47.6072 |
|
- Rougelsum: 47.5635 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
|
| No log | 1.0 | 17 | 0.1238 | 46.7806 | 30.4394 | 36.8259 | 36.8757 | |
|
| 0.4762 | 2.0 | 34 | 0.1058 | 49.4907 | 32.4075 | 39.352 | 39.161 | |
|
| 0.4762 | 3.0 | 51 | 0.0899 | 54.1557 | 35.6198 | 41.6488 | 41.4013 | |
|
| 0.1104 | 4.0 | 68 | 0.0867 | 53.237 | 36.766 | 42.8508 | 42.7151 | |
|
| 0.1104 | 5.0 | 85 | 0.0773 | 57.4084 | 39.3354 | 45.068 | 44.9505 | |
|
| 0.0914 | 6.0 | 102 | 0.0736 | 56.9111 | 41.3118 | 48.1607 | 47.9965 | |
|
| 0.0914 | 7.0 | 119 | 0.0699 | 58.6135 | 42.3985 | 48.7923 | 48.4873 | |
|
| 0.0785 | 8.0 | 136 | 0.0673 | 59.5593 | 43.9205 | 51.7275 | 51.5617 | |
|
| 0.0785 | 9.0 | 153 | 0.0618 | 62.0583 | 47.3928 | 53.3198 | 53.1472 | |
|
| 0.0702 | 10.0 | 170 | 0.0612 | 55.9874 | 41.0458 | 47.6072 | 47.5635 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|