Downloads · 30 days
3
13% of all-time downloads
mt5_base_EN_sch_wiki
e22vvb/mt5_base_EN_sch_wiki
mt5_base_EN_sch_wiki is a machine learning model from e22vvb. 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
24
Public
Parameters
582M
4.7 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin2.3 GB · 50%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- mt5
- Access
- Public
- Created
- Nov 9, 2024
- Updated
- Nov 10, 2024
- SHA
- caf847bc
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. -->
mt5_base_EN_sch_wiki
This model is a fine-tuned version of google/mt5-base on the wikisql dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Rouge2 Precision: 0.0165
- Rouge2 Recall: 0.0087
- Rouge2 Fmeasure: 0.0111
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: 5e-05
- train_batch_size: 14
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.0 | 1.0 | 4627 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 2.0 | 9254 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 3.0 | 13881 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 4.0 | 18508 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 5.0 | 23135 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 6.0 | 27762 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 7.0 | 32389 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 8.0 | 37016 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 9.0 | 41643 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 10.0 | 46270 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 11.0 | 50897 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 12.0 | 55524 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 13.0 | 60151 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 14.0 | 64778 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 15.0 | 69405 | nan | 0.0165 | 0.0087 | 0.0111 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.2.2
- Datasets 2.16.1
- Tokenizers 0.20.3
- Library
- transformers
- Type
- mt5
- License
- apache-2.0
- Created
- Nov 9, 2024
- Updated
- Nov 10, 2024