Downloads · 30 days
2
1% of all-time downloads
finetune-newwiki-summarization-ver-augmented
minnehwg/finetune-newwiki-summarization-ver-augmented
finetune-newwiki-summarization-ver-augmented is a machine learning model from minnehwg. 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 mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
357
Public
Repo size
7.2 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin904 MB · 100%
At a glance
- Library
- transformers
- License
- mit
- Model type
- t5
- Access
- Public
- Created
- May 15, 2024
- Updated
- May 15, 2024
- SHA
- 5689f6b2
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. -->
finetune-newwiki-summarization-ver-augmented
This model is a fine-tuned version of VietAI/vit5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4282
- Rouge1: 48.7749
- Rouge2: 26.3665
- Rougel: 35.7765
- Rougelsum: 38.0111
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: 1e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 0.6784 | 1.0 | 2312 | 0.5136 | 46.7374 | 23.3000 | 33.5379 | 35.8923 |
| 0.6015 | 2.0 | 4624 | 0.4759 | 47.7112 | 24.5817 | 34.4939 | 36.9831 |
| 0.5587 | 3.0 | 6936 | 0.4543 | 48.4891 | 25.6592 | 35.2310 | 37.5477 |
| 0.5128 | 4.0 | 9248 | 0.4405 | 48.7777 | 26.0690 | 35.5187 | 37.7896 |
| 0.4899 | 5.0 | 11560 | 0.4338 | 48.6758 | 26.0670 | 35.5783 | 37.8850 |
| 0.4796 | 6.0 | 13872 | 0.4295 | 48.8914 | 26.5018 | 35.8671 | 38.1289 |
| 0.4671 | 7.0 | 16184 | 0.4282 | 48.7749 | 26.3665 | 35.7765 | 38.0111 |
Framework versions
- Transformers 4.17.0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- t5
- License
- mit
- Created
- May 15, 2024
- Updated
- May 15, 2024