File size: 2,325 Bytes
44f6fbf |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 |
---
license: mit
base_model: facebook/bart-large-cnn
tags:
- summarization
- generated_from_trainer
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-scientific-articles
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: scientific_papers
type: scientific_papers
config: pubmed
split: train
args: pubmed
metrics:
- name: Rouge1
type: rouge
value: 34.2136
---
<!-- 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-scientific-articles
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the scientific_papers dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6416
- Rouge1: 34.2136
- Rouge2: 11.6215
- Rougel: 20.2516
- Rougelsum: 30.6019
## 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: 9
- eval_batch_size: 9
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 3.3695 | 1.0 | 56 | 2.8464 | 32.133 | 10.3816 | 18.7538 | 29.311 |
| 2.7639 | 2.0 | 112 | 2.6667 | 31.5794 | 10.8708 | 19.2408 | 28.6171 |
| 2.517 | 3.0 | 168 | 2.6220 | 33.1806 | 11.2477 | 19.7199 | 30.1012 |
| 2.2989 | 4.0 | 224 | 2.6031 | 32.7604 | 10.9356 | 19.4766 | 29.6503 |
| 2.0883 | 5.0 | 280 | 2.6416 | 34.2136 | 11.6215 | 20.2516 | 30.6019 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|