Downloads · 30 days
7
16% of all-time downloads
md_mt5_base_boun_split_second_v1_retrain_on_second_imst
Buseak/md_mt5_base_boun_split_second_v1_retrain_on_second_imst
md_mt5_base_boun_split_second_v1_retrain_on_second_imst is a machine learning model from Buseak. 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
43
Public
Parameters
300M
18 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.2 GB · 98%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- mt5
- Access
- Public
- Created
- Dec 10, 2023
- Updated
- Dec 10, 2023
- SHA
- 667ce6c3
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. -->
md_mt5_base_boun_split_second_v1_retrain_on_second_imst
This model is a fine-tuned version of Buseak/md_mt5_base_boun_split_second_v1_retrain_on_first_boun on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1581
- Bleu: 2.0954
- Gen Len: 18.7592
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: 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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 0.5133 | 1.0 | 916 | 0.2581 | 1.8828 | 18.7472 |
| 0.4699 | 2.0 | 1832 | 0.2371 | 1.9073 | 18.7142 |
| 0.4469 | 3.0 | 2748 | 0.2222 | 1.9197 | 18.739 |
| 0.4205 | 4.0 | 3664 | 0.2085 | 1.9502 | 18.7502 |
| 0.4001 | 5.0 | 4580 | 0.1983 | 1.9643 | 18.7409 |
| 0.3992 | 6.0 | 5496 | 0.1898 | 1.9948 | 18.7633 |
| 0.3824 | 7.0 | 6412 | 0.1841 | 2.0136 | 18.7614 |
| 0.3666 | 8.0 | 7328 | 0.1766 | 2.0422 | 18.7649 |
| 0.3562 | 9.0 | 8244 | 0.1713 | 2.0554 | 18.7636 |
| 0.345 | 10.0 | 9160 | 0.1672 | 2.0659 | 18.7611 |
| 0.3465 | 11.0 | 10076 | 0.1637 | 2.0804 | 18.7611 |
| 0.3303 | 12.0 | 10992 | 0.1617 | 2.0815 | 18.7619 |
| 0.3333 | 13.0 | 11908 | 0.1594 | 2.0835 | 18.7592 |
| 0.328 | 14.0 | 12824 | 0.1581 | 2.0958 | 18.7592 |
| 0.3267 | 15.0 | 13740 | 0.1581 | 2.0954 | 18.7592 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Library
- transformers
- Type
- mt5
- License
- apache-2.0
- Created
- Dec 10, 2023
- Updated
- Dec 10, 2023