metadata
tags:
- generated_from_trainer
datasets:
- hotpot_qa
metrics:
- rouge
model-index:
- name: bart-qg-finetuned-hotpotqa
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: hotpot_qa
type: hotpot_qa
config: distractor
split: train
args: distractor
metrics:
- name: Rouge1
type: rouge
value: 46.2814
bart-qg-finetuned-hotpotqa
This model is a fine-tuned version of p208p2002/bart-squad-qg-hl on the hotpot_qa dataset. It achieves the following results on the evaluation set:
- Loss: 1.0817
- Rouge1: 46.2814
- Rouge2: 30.4609
- Rougel: 42.3385
- Rougelsum: 42.3741
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
1.3949 | 1.0 | 2500 | 1.1812 | 44.0967 | 28.022 | 40.0397 | 40.0403 |
1.0883 | 2.0 | 5000 | 1.1141 | 44.9629 | 29.1863 | 41.1078 | 41.1684 |
0.8677 | 3.0 | 7500 | 1.0817 | 46.2814 | 30.4609 | 42.3385 | 42.3741 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2