|
--- |
|
license: mit |
|
base_model: facebook/bart-large-cnn |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- clupubhealth |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: bart-cnn-pubhealth-expanded-hi-grad |
|
results: |
|
- task: |
|
name: Sequence-to-sequence Language Modeling |
|
type: text2text-generation |
|
dataset: |
|
name: clupubhealth |
|
type: clupubhealth |
|
config: expanded |
|
split: test |
|
args: expanded |
|
metrics: |
|
- name: Rouge1 |
|
type: rouge |
|
value: 28.8807 |
|
--- |
|
|
|
<!-- 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-cnn-pubhealth-expanded-hi-grad |
|
|
|
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the clupubhealth dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.1939 |
|
- Rouge1: 28.8807 |
|
- Rouge2: 8.9567 |
|
- Rougel: 19.5591 |
|
- Rougelsum: 20.6726 |
|
- Gen Len: 66.99 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 950 |
|
- total_train_batch_size: 15200 |
|
- 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 | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| |
|
| 3.4166 | 0.49 | 2 | 2.4019 | 22.0991 | 4.6789 | 15.1628 | 17.4382 | 75.065 | |
|
| 3.2194 | 0.98 | 4 | 2.3372 | 25.0981 | 6.6975 | 17.4606 | 19.2018 | 71.225 | |
|
| 3.0969 | 1.47 | 6 | 2.2979 | 26.4747 | 7.1948 | 18.2262 | 19.6241 | 67.19 | |
|
| 3.0313 | 1.96 | 8 | 2.3038 | 26.8637 | 7.5831 | 18.2923 | 19.6327 | 66.875 | |
|
| 2.9753 | 2.44 | 10 | 2.2976 | 27.8942 | 8.3434 | 19.095 | 20.6248 | 67.975 | |
|
| 2.9296 | 2.93 | 12 | 2.2602 | 28.1255 | 8.6477 | 19.0575 | 20.7787 | 68.515 | |
|
| 2.8681 | 3.42 | 14 | 2.2341 | 28.0812 | 8.598 | 19.3391 | 20.7526 | 68.285 | |
|
| 2.867 | 3.91 | 16 | 2.2246 | 28.3624 | 8.7921 | 19.5552 | 21.1147 | 68.225 | |
|
| 2.8157 | 4.4 | 18 | 2.2178 | 28.8197 | 8.8423 | 19.3606 | 20.698 | 69.08 | |
|
| 2.8007 | 4.89 | 20 | 2.2149 | 28.34 | 8.5084 | 18.8293 | 20.1169 | 68.255 | |
|
| 2.7797 | 5.38 | 22 | 2.2123 | 28.2156 | 8.4891 | 19.3472 | 20.5036 | 67.525 | |
|
| 2.7563 | 5.87 | 24 | 2.2083 | 27.8927 | 8.3783 | 19.1194 | 20.2498 | 68.365 | |
|
| 2.736 | 6.36 | 26 | 2.2035 | 28.2588 | 8.2345 | 18.9418 | 20.2931 | 68.335 | |
|
| 2.7208 | 6.85 | 28 | 2.2020 | 28.2471 | 8.599 | 19.3465 | 20.5104 | 68.44 | |
|
| 2.713 | 7.33 | 30 | 2.2022 | 28.1863 | 8.5142 | 19.194 | 20.2467 | 68.3 | |
|
| 2.7135 | 7.82 | 32 | 2.2013 | 28.462 | 8.6346 | 19.2465 | 20.4812 | 68.195 | |
|
| 2.6987 | 8.31 | 34 | 2.1988 | 28.9168 | 8.8888 | 19.6491 | 20.7796 | 67.275 | |
|
| 2.6978 | 8.8 | 36 | 2.1965 | 28.7303 | 8.9879 | 19.5924 | 20.6943 | 67.31 | |
|
| 2.6769 | 9.29 | 38 | 2.1946 | 28.7956 | 8.9652 | 19.545 | 20.7352 | 67.33 | |
|
| 2.6821 | 9.78 | 40 | 2.1939 | 28.8807 | 8.9567 | 19.5591 | 20.6726 | 66.99 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.7.1 |
|
- Tokenizers 0.13.2 |
|
|
