metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- kp20k
metrics:
- rouge
model-index:
- name: keyphrase-extractions_bart-large
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: kp20k
type: kp20k
config: generation
split: train[:15%]
args: generation
metrics:
- name: Rouge1
type: rouge
value: 0.4713
keyphrase-extractions_bart-large
This model is a fine-tuned version of facebook/bart-large on the kp20k dataset. It achieves the following results on the evaluation set:
- Loss: 1.7257
- Rouge1: 0.4713
- Rouge2: 0.2385
- Rougel: 0.384
- Rougelsum: 0.3841
- Gen Len: 18.3164
- Phrase match: 0.1917
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Phrase match |
|---|---|---|---|---|---|---|---|---|---|
| 2.5104 | 1.0 | 730 | 1.8021 | 0.464 | 0.2336 | 0.3765 | 0.3766 | 18.9074 | 0.1784 |
| 1.8436 | 2.0 | 1460 | 1.7473 | 0.4709 | 0.2381 | 0.3834 | 0.3836 | 17.8127 | 0.1891 |
| 1.6864 | 3.0 | 2190 | 1.7257 | 0.4713 | 0.2385 | 0.384 | 0.3841 | 18.3164 | 0.1917 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2