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KGAQ-2
rausch/KGAQ-2
KGAQ-2 is a machine learning model from rausch. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Aug 2, 2024
- Updated
- Aug 3, 2024
- SHA
- 62b0dbf2
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. -->
KGAQ-2
This model is a fine-tuned version of google/flan-t5-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.6712
- Rouge1: 9.9002
- Rouge2: 0.817
- Rougel: 9.31
- Rougelsum: 9.8757
- Gen Len: 4.0
- F1: 0.0005
- Recall: 0.0008
- Precision: 0.0003
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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 3.5701 | 1.0 | 598 | 3.3914 | 14.1052 | 1.2078 | 13.0257 | 14.1332 | 3.0 | 0.0 | 0.0 | 0.0 |
| 3.0379 | 2.0 | 1196 | 2.7468 | 12.4379 | 1.0435 | 11.3645 | 12.4814 | 3.0 | 0.0005 | 0.0008 | 0.0003 |
| 2.2773 | 3.0 | 1794 | 2.4962 | 25.6591 | 2.6653 | 16.5422 | 25.687 | 6.0 | 0.0 | 0.0 | 0.0 |
| 1.8845 | 4.0 | 2392 | 2.4370 | 8.8131 | 0.2887 | 8.1866 | 8.8014 | 3.0 | 0.0005 | 0.0008 | 0.0003 |
| 1.7721 | 5.0 | 2990 | 2.5342 | 8.2864 | 0.5105 | 7.6569 | 8.2655 | 3.0 | 0.0005 | 0.0008 | 0.0003 |
| 2.1007 | 6.0 | 3588 | 2.5028 | 27.8343 | 3.8693 | 19.0586 | 27.8325 | 6.4795 | 0.0022 | 0.0036 | 0.0015 |
| 2.0255 | 7.0 | 4186 | 2.5544 | 8.2864 | 0.5105 | 7.6569 | 8.2655 | 3.0 | 0.0005 | 0.0008 | 0.0003 |
| 1.9177 | 8.0 | 4784 | 2.5356 | 22.6347 | 3.1887 | 14.2667 | 22.6751 | 7.0 | 0.0005 | 0.0008 | 0.0003 |
| 1.7165 | 9.0 | 5382 | 2.5492 | 9.9002 | 0.817 | 9.31 | 9.8757 | 4.0 | 0.0005 | 0.0008 | 0.0003 |
| 1.645 | 10.0 | 5980 | 2.6712 | 9.9002 | 0.817 | 9.31 | 9.8757 | 4.0 | 0.0005 | 0.0008 | 0.0003 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- t5
- License
- apache-2.0
- Created
- Aug 2, 2024
- Updated
- Aug 3, 2024