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--- |
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license: cc-by-sa-4.0 |
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base_model: retrieva-jp/t5-base-long |
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tags: |
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- generated_from_trainer |
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- summarization |
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datasets: |
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- xlsum |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-base-xlsum-ja |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: csebuetnlp/xlsum |
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type: XL-Sum |
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config: japanese |
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split: train |
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args: japanese |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.3648008957585529 |
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- name: Rouge2 |
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type: rouge |
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value: 0.16411161798042992 |
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language: |
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- ja |
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library_name: transformers |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# t5-base-xlsum-ja |
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This model is a fine-tuned version of [retrieva-jp/t5-base-long](https://huggingface.co/retrieva-jp/t5-base-long) on the xlsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6563 |
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- Rouge1: 0.3648 |
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- Rouge2: 0.1641 |
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- Rougel: 0.2965 |
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- Rougelsum: 0.3132 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.01 |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
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| 4.9166 | 1.8 | 100 | 3.4095 | 0.3569 | 0.1509 | 0.2416 | 0.3209 | |
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| 4.1162 | 3.61 | 200 | 3.0980 | 0.3262 | 0.1354 | 0.2557 | 0.2805 | |
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| 3.8578 | 5.41 | 300 | 2.8853 | 0.3428 | 0.1445 | 0.2628 | 0.2881 | |
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| 3.7309 | 7.22 | 400 | 2.7714 | 0.3621 | 0.1615 | 0.2951 | 0.3151 | |
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| 3.6716 | 9.02 | 500 | 2.7042 | 0.3727 | 0.1668 | 0.2982 | 0.3225 | |
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| 3.6393 | 10.82 | 600 | 2.6666 | 0.3676 | 0.1592 | 0.2987 | 0.3206 | |
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| 3.6291 | 12.63 | 700 | 2.6587 | 0.3654 | 0.1576 | 0.2955 | 0.3108 | |
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| 3.6224 | 14.43 | 800 | 2.6563 | 0.3648 | 0.1641 | 0.2965 | 0.3132 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
