transformers safetensors mbart text2text-generation generated_from_trainer dataset:xlsum base_model:ku-nlp/bart-base-japanese license:cc-by-sa-4.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: cc-by-sa-4.0
base_model: ku-nlp/bart-base-japanese
tags:
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: bart-base-japanese-5174-japanese
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xlsum
      type: xlsum
      config: japanese
      split: validation
      args: japanese
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.0
---

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# bart-base-japanese-5174-japanese

This model is a fine-tuned version of [ku-nlp/bart-base-japanese](https://huggingface.co/ku-nlp/bart-base-japanese) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2680
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
- Gen Len: 20.0

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.6687        | 4.5   | 500  | 1.4936          | 0.0    | 0.0    | 0.0    | 0.0       | 19.9978 |
| 1.3462        | 8.99  | 1000 | 1.2680          | 0.0    | 0.0    | 0.0    | 0.0       | 20.0    |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
