metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum-xlsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: scientific_papers
type: scientific_papers
config: pubmed
split: train
args: pubmed
metrics:
- name: Rouge1
type: rouge
value: 14.3541
t5-small-finetuned-xsum-xlsum
This model is a fine-tuned version of t5-small on the scientific_papers dataset. It achieves the following results on the evaluation set:
- Loss: 1.9963
- Rouge1: 14.3541
- Rouge2: 6.1674
- Rougel: 12.2975
- Rougelsum: 13.2515
- Gen Len: 19.0
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.3055 | 1.0 | 7496 | 2.0773 | 14.3312 | 6.153 | 12.2551 | 13.2033 | 19.0 |
| 2.2512 | 2.0 | 14992 | 2.0330 | 14.3048 | 6.1346 | 12.2343 | 13.1992 | 19.0 |
| 2.2034 | 3.0 | 22488 | 2.0106 | 14.3866 | 6.1752 | 12.3205 | 13.2743 | 19.0 |
| 2.2054 | 4.0 | 29984 | 2.0004 | 14.3629 | 6.167 | 12.2928 | 13.2506 | 19.0 |
| 2.1944 | 5.0 | 37480 | 1.9963 | 14.3541 | 6.1674 | 12.2975 | 13.2515 | 19.0 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2