Downloads · 30 days
3
2% of all-time downloads
ks-chungcheong-nmt-v2
smile3634/ks-chungcheong-nmt-v2
ks-chungcheong-nmt-v2 is a machine learning model from smile3634. 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.
should probably proofread and complete it, then remove this comment. --
All-time downloads
181
Public
Repo size
13.5 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin751 MB · 100%
At a glance
- Library
- transformers
- Model type
- encoder-decoder
- Access
- Public
- Created
- Jan 31, 2023
- Updated
- Jan 31, 2023
- SHA
- bc2aa5c1
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. -->
ks-chungcheong-nmt-v2
This model is a fine-tuned version of smile3634/ks-chungcheong-nmt-v1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2771
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: 16
- eval_batch_size: 16
- 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.8849 | 0.16 | 500 | 1.8573 |
| 1.7337 | 0.32 | 1000 | 1.6565 |
| 1.5085 | 0.49 | 1500 | 1.2008 |
| 1.1849 | 0.65 | 2000 | 0.8869 |
| 0.9535 | 0.81 | 2500 | 0.6806 |
| 0.8032 | 0.97 | 3000 | 0.5774 |
| 0.5472 | 1.13 | 3500 | 0.5094 |
| 0.4656 | 1.29 | 4000 | 0.4570 |
| 0.4269 | 1.46 | 4500 | 0.4286 |
| 0.3916 | 1.62 | 5000 | 0.4011 |
| 0.3564 | 1.78 | 5500 | 0.3676 |
| 0.3259 | 1.94 | 6000 | 0.3422 |
| 0.2513 | 2.1 | 6500 | 0.3312 |
| 0.2101 | 2.26 | 7000 | 0.3111 |
| 0.1991 | 2.43 | 7500 | 0.2985 |
| 0.1893 | 2.59 | 8000 | 0.2960 |
| 0.1774 | 2.75 | 8500 | 0.2823 |
| 0.1687 | 2.91 | 9000 | 0.2771 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Tokenizers 0.13.2
- Library
- transformers
- Type
- encoder-decoder
- Created
- Jan 31, 2023
- Updated
- Jan 31, 2023