Downloads · 30 days
36
2% of all-time downloads
t5-large-finetune-keyword-to-text-generation
caffsean/t5-large-finetune-keyword-to-text-generation
t5-large-finetune-keyword-to-text-generation is a machine learning model from caffsean. 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. --
All-time downloads
1.7K
Public
Repo size
14.8 GB
Likes
2
Public
Repo makeup
Click a slice to open those files.
.bin3 GB · 100%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Aug 29, 2022
- Updated
- Sep 1, 2022
- SHA
- 239b010e
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. -->
t5-large-finetune-keyword-to-text-generation
This model is a fine-tuned version of t5-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.1471
- Rouge1: 2.175
- Rouge2: 0.3661
- Rougel: 1.7927
- Rougelsum: 1.7951
- Gen Len: 15.3252
Model description
This model is designed to generate text from a single keyword. This project is intended to be used for generating vocabulary questions for ed-tech applications.
NOTE!: Be sure to use the 'summarize: ' prefix before the word that you would like to un-summarize.
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.3083 | 1.0 | 3000 | 3.1706 | 2.1498 | 0.331 | 1.7579 | 1.761 | 16.6826 |
| 3.2121 | 2.0 | 6000 | 3.1403 | 2.1555 | 0.3409 | 1.7659 | 1.769 | 16.208 |
| 3.1286 | 3.0 | 9000 | 3.1300 | 2.1577 | 0.3511 | 1.7703 | 1.7733 | 15.9009 |
| 3.0567 | 4.0 | 12000 | 3.1282 | 2.183 | 0.3584 | 1.7895 | 1.7909 | 15.7135 |
| 2.9953 | 5.0 | 15000 | 3.1293 | 2.1589 | 0.3525 | 1.776 | 1.7781 | 15.678 |
| 2.9483 | 6.0 | 18000 | 3.1308 | 2.1645 | 0.3556 | 1.7824 | 1.784 | 15.425 |
| 2.9009 | 7.0 | 21000 | 3.1358 | 2.1622 | 0.3622 | 1.7848 | 1.7877 | 15.3348 |
| 2.8752 | 8.0 | 24000 | 3.1387 | 2.1716 | 0.36 | 1.7936 | 1.7963 | 15.5296 |
| 2.835 | 9.0 | 27000 | 3.1454 | 2.1806 | 0.3658 | 1.7941 | 1.7966 | 15.4625 |
| 2.8352 | 10.0 | 30000 | 3.1471 | 2.175 | 0.3661 | 1.7927 | 1.7951 | 15.3252 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Aug 29, 2022
- Updated
- Sep 1, 2022