metadata
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
datasets:
- scientific_papers
model-index:
- name: models
results: []
models
This model is a fine-tuned version of facebook/bart-large-cnn on the scientific_papers dataset. It achieves the following results on the evaluation set:
- Loss: 2.6842
- Rouge2 Precision: 0.1282
- Rouge2 Recall: 0.1133
- Rouge2 Fmeasure: 0.1186
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 2.9888 | 0.32 | 10 | 2.8091 | 0.1445 | 0.1158 | 0.1251 |
| 2.7186 | 0.64 | 20 | 2.6898 | 0.1332 | 0.1183 | 0.1232 |
| 2.6847 | 0.96 | 30 | 2.6861 | 0.1291 | 0.1144 | 0.1197 |
Framework versions
- Transformers 4.37.2
- Pytorch 1.13.1
- Datasets 2.16.1
- Tokenizers 0.15.2