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ke_t5_small_nikl_summarization
chunwoolee0/ke_t5_small_nikl_summarization
ke_t5_small_nikl_summarization is a machine learning model from chunwoolee0. 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
- Sep 17, 2023
- Updated
- Sep 17, 2023
- SHA
- 95e20bad
Base models
Datasets
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. -->
ke_t5_small_nikl_summarization
This model is a fine-tuned version of KETI-AIR/ke-t5-small on the summary_and_report dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
- Gen Len: 0.0
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.0 | 1.0 | 4594 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0 | 2.0 | 9188 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0 | 3.0 | 13782 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Sep 17, 2023
- Updated
- Sep 17, 2023