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mt5-summarize-ja
tym24/mt5-summarize-ja
mt5-summarize-ja is a machine learning model from tym24. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- mt5
- Access
- Public
- Created
- Feb 19, 2024
- Updated
- Feb 19, 2024
- SHA
- 23befcbe
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
mt5-summarize-ja
This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.0695
- Rouge1: 0.3667
- Rouge2: 0.1678
- Rougel: 0.2998
- Rougelsum: 0.3123
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: 0.0005
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 90
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 3.3241 | 0.7 | 100 | 2.4795 | 0.2943 | 0.1245 | 0.2472 | 0.2471 |
| 2.7583 | 1.4 | 200 | 2.2710 | 0.3054 | 0.1152 | 0.2539 | 0.2576 |
| 2.5469 | 2.1 | 300 | 2.2936 | 0.3446 | 0.1493 | 0.2808 | 0.2887 |
| 2.5335 | 2.8 | 400 | 2.1913 | 0.3228 | 0.1270 | 0.2665 | 0.2725 |
| 2.4383 | 3.5 | 500 | 2.1507 | 0.3630 | 0.1671 | 0.3082 | 0.3144 |
| 2.3671 | 4.2 | 600 | 2.1338 | 0.3388 | 0.1493 | 0.2814 | 0.2880 |
| 2.349 | 4.9 | 700 | 2.1089 | 0.3621 | 0.1576 | 0.2980 | 0.3079 |
| 2.264 | 5.6 | 800 | 2.1353 | 0.3740 | 0.1784 | 0.3083 | 0.3157 |
| 2.1577 | 6.3 | 900 | 2.1101 | 0.3711 | 0.1716 | 0.3107 | 0.3166 |
| 2.1315 | 7.0 | 1000 | 2.0905 | 0.3862 | 0.1826 | 0.3198 | 0.3269 |
| 2.1418 | 7.7 | 1100 | 2.0893 | 0.3433 | 0.1621 | 0.2895 | 0.2963 |
| 2.0744 | 8.4 | 1200 | 2.0881 | 0.3778 | 0.1834 | 0.3130 | 0.3242 |
| 2.0944 | 9.1 | 1300 | 2.0709 | 0.3676 | 0.1688 | 0.3024 | 0.3140 |
| 2.1015 | 9.8 | 1400 | 2.0695 | 0.3667 | 0.1678 | 0.2998 | 0.3123 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- mt5
- License
- apache-2.0
- Created
- Feb 19, 2024
- Updated
- Feb 19, 2024