Japanese Summarization
Collection
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Updated
mt5-base-xlsum-ja
This model is a fine-tuned version of google/mt5-base on the xlsum dataset.
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 90
- num_epochs: 10
Training results
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
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Model tree for p1atdev/mt5-base-xlsum-ja
Base model
google/mt5-base
Finetuned
this model
Dataset used to train p1atdev/mt5-base-xlsum-ja
Collection including p1atdev/mt5-base-xlsum-ja
Evaluation results
- Rouge1 on csebuetnlp/xlsumtest set self-reported0.329
- Rouge2 on csebuetnlp/xlsumtest set self-reported0.165
- RougeL on csebuetnlp/xlsumtest set self-reported0.250