README.md

metadata

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

bart-base-japanese-5174-japanese

This model is a fine-tuned version of 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