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kdrt_content
brescia/kdrt_content
kdrt_content is a text classification model from brescia. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Mar 19, 2024
- Updated
- Apr 27, 2024
- SHA
- 6f71ffbc
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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. -->
kdrt_content
This model is a fine-tuned version of indobenchmark/indobert-base-p1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2446
- Accuracy: 0.9231
- Precision: 0.9231
- Recall: 0.9231
- F1: 0.9231
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 59 | 0.4204 | 0.8291 | 0.8291 | 0.8291 | 0.8291 |
| No log | 2.0 | 118 | 0.2446 | 0.9231 | 0.9231 | 0.9231 | 0.9231 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Mar 19, 2024
- Updated
- Apr 27, 2024