metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xlsum-chinese-tradition
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xlsum
type: xlsum
args: chinese_traditional
metrics:
- name: Rouge1
type: rouge
value: 0.7966
t5-small-finetuned-xlsum-chinese-tradition
This model is a fine-tuned version of t5-small on the xlsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.2848
- Rouge1: 0.7966
- Rouge2: 0.0942
- Rougel: 0.7989
- Rougelsum: 0.7967
- Gen Len: 7.0854
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: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
1.4457 | 1.0 | 2336 | 1.2848 | 0.7966 | 0.0942 | 0.7989 | 0.7967 | 7.0854 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1