metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- scientific_papers
metrics:
- rouge
base_model: facebook/bart-base
model-index:
- name: bart-base-finetuned-pubmed
results:
- task:
type: text2text-generation
name: Sequence-to-sequence Language Modeling
dataset:
name: scientific_papers
type: scientific_papers
args: pubmed
metrics:
- type: rouge
value: 9.1984
name: Rouge1
bart-base-finetuned-pubmed
This model is a fine-tuned version of facebook/bart-base on the scientific_papers dataset. It achieves the following results on the evaluation set:
- Loss: 1.9804
- Rouge1: 9.1984
- Rouge2: 4.3091
- Rougel: 7.9739
- Rougelsum: 8.6759
- Gen Len: 20.0
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.2869 | 1.0 | 29981 | 2.1241 | 9.0852 | 4.1152 | 7.842 | 8.5395 | 20.0 |
| 2.1469 | 2.0 | 59962 | 2.0225 | 9.1609 | 4.2437 | 7.9311 | 8.6273 | 20.0 |
| 2.113 | 3.0 | 89943 | 1.9959 | 9.3086 | 4.3305 | 8.0363 | 8.7713 | 20.0 |
| 2.0632 | 4.0 | 119924 | 1.9804 | 9.1984 | 4.3091 | 7.9739 | 8.6759 | 20.0 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.1+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3