metadata
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
bart-cnn-pubhealth-expanded-hi-grad
This model is a fine-tuned version of 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