metadata
license: mit
tags:
- generated_from_trainer
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: bart-large-cnn-pubmed1o3-pubmed2o3-pubmed3o3
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: scientific_papers
type: scientific_papers
args: pubmed
metrics:
- name: Rouge1
type: rouge
value: 37.5622
bart-large-cnn-pubmed1o3-pubmed2o3-pubmed3o3
This model is a fine-tuned version of theojolliffe/bart-large-cnn-pubmed1o3-pubmed2o3 on the scientific_papers dataset. It achieves the following results on the evaluation set:
- Loss: 1.8540
- Rouge1: 37.5622
- Rouge2: 15.5848
- Rougel: 23.1384
- Rougelsum: 34.2695
- Gen Len: 138.0326
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
1.9205 | 1.0 | 19987 | 1.8540 | 37.5622 | 15.5848 | 23.1384 | 34.2695 | 138.0326 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1