Downloads · 30 days
15
3% of all-time downloads
BARTkrame-abstract-mT5
krm/BARTkrame-abstract-mT5
BARTkrame-abstract-mT5 is a summarization model from krm. Use it when you need a shorter version of a longer text. 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
455
Public
Repo size
3.6 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.2 GB · 98%
At a glance
- Task
- Summarization
- Library
- transformers
- License
- apache-2.0
- Model type
- mt5
- Access
- Public
- Created
- Oct 15, 2022
- Updated
- Oct 15, 2022
- SHA
- 224127ec
Try a prompt
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. -->
BARTkrame-abstract-mT5
This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2557
- Rouge1: 0.2223
- Rouge2: 0.0735
- Rougel: 0.1826
- Rougelsum: 0.1849
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: 5.6e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 4.9563 | 1.0 | 1250 | 2.3674 | 0.2206 | 0.0755 | 0.1853 | 0.1869 |
| 3.1856 | 2.0 | 2500 | 2.2988 | 0.2296 | 0.0757 | 0.1888 | 0.1910 |
| 3.0083 | 3.0 | 3750 | 2.2668 | 0.2201 | 0.0728 | 0.1816 | 0.1832 |
| 2.9296 | 4.0 | 5000 | 2.2557 | 0.2223 | 0.0735 | 0.1826 | 0.1849 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
- Task
- Summarization
- Library
- transformers
- Type
- mt5
- License
- apache-2.0
- Created
- Oct 15, 2022
- Updated
- Oct 15, 2022