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ALL_manual_mt5-base_15_spider_no_sch_15
NatthawatTung/ALL_manual_mt5-base_15_spider_no_sch_15
ALL_manual_mt5-base_15_spider_no_sch_15 is a machine learning model from NatthawatTung. 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
- t5
- Access
- Public
- Created
- Jun 19, 2024
- Updated
- Jun 20, 2024
- SHA
- b3280d55
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. -->
ALL_manual_mt5-base_15_spider_no_sch_15
This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0378
- Rouge2 Precision: 0.7495
- Rouge2 Recall: 0.5027
- Rouge2 Fmeasure: 0.5711
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: 15
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 1.7943 | 1.0 | 1293 | 0.3227 | 0.2802 | 0.1766 | 0.1964 |
| 0.2825 | 2.0 | 2586 | 0.1790 | 0.4482 | 0.2731 | 0.318 |
| 0.2224 | 3.0 | 3879 | 0.1336 | 0.5122 | 0.3371 | 0.3817 |
| 0.1691 | 4.0 | 5172 | 0.1052 | 0.5597 | 0.3717 | 0.4211 |
| 0.1483 | 5.0 | 6465 | 0.0861 | 0.6096 | 0.4062 | 0.4603 |
| 0.1261 | 6.0 | 7758 | 0.0735 | 0.6317 | 0.4226 | 0.4787 |
| 0.1088 | 7.0 | 9051 | 0.0637 | 0.6726 | 0.4493 | 0.5099 |
| 0.1015 | 8.0 | 10344 | 0.0569 | 0.688 | 0.462 | 0.5237 |
| 0.0915 | 9.0 | 11637 | 0.0512 | 0.6945 | 0.4626 | 0.526 |
| 0.0865 | 10.0 | 12930 | 0.0469 | 0.7244 | 0.4879 | 0.5529 |
| 0.0799 | 11.0 | 14223 | 0.0439 | 0.7377 | 0.495 | 0.5615 |
| 0.0757 | 12.0 | 15516 | 0.0413 | 0.743 | 0.4983 | 0.5659 |
| 0.074 | 13.0 | 16809 | 0.0393 | 0.749 | 0.5028 | 0.5707 |
| 0.0718 | 14.0 | 18102 | 0.0382 | 0.7485 | 0.5018 | 0.5701 |
| 0.0708 | 15.0 | 19395 | 0.0378 | 0.7495 | 0.5027 | 0.5711 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.3
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Jun 19, 2024
- Updated
- Jun 20, 2024