---
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: 0.8887
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# t5-small-finetuned-xlsum-chinese-tradition

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2061
- Rouge1: 0.8887
- Rouge2: 0.0671
- Rougel: 0.889
- Rougelsum: 0.8838
- Gen Len: 6.8779

## 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: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.4231        | 1.0   | 2336  | 1.2586          | 0.711  | 0.0528 | 0.7029 | 0.7053    | 7.3368  |
| 1.378         | 2.0   | 4672  | 1.2281          | 0.9688 | 0.05   | 0.9574 | 0.9656    | 7.0392  |
| 1.3567        | 3.0   | 7008  | 1.2182          | 0.9534 | 0.1035 | 0.9531 | 0.9472    | 6.7437  |
| 1.3339        | 4.0   | 9344  | 1.2096          | 0.9969 | 0.0814 | 0.9969 | 0.9938    | 7.4503  |
| 1.3537        | 5.0   | 11680 | 1.2072          | 0.8429 | 0.0742 | 0.8372 | 0.838     | 6.8049  |
| 1.3351        | 6.0   | 14016 | 1.2061          | 0.8887 | 0.0671 | 0.889  | 0.8838    | 6.8779  |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1