Downloads · 30 days
38
9% of all-time downloads
Contract-base-tokenizer-KR-FinBert
cheongmyeong17/Contract-base-tokenizer-KR-FinBert
Contract-base-tokenizer-KR-FinBert is a text classification model from cheongmyeong17. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
432
Public
Repo size
1.6 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin406 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Feb 13, 2023
- Updated
- Feb 13, 2023
- SHA
- 6396585e
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. -->
Contract-base-tokenizer-KR-FinBert
This model is a fine-tuned version of snunlp/KR-FinBert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0694
- Accuracy: 0.9859
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 249 | 0.0563 | 0.9849 |
| No log | 2.0 | 498 | 0.0590 | 0.9849 |
| No log | 3.0 | 747 | 0.0694 | 0.9859 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Feb 13, 2023
- Updated
- Feb 13, 2023