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digidaw
bwahyuh/digidaw
digidaw is a text classification model from bwahyuh. Use it when you need a label for a piece of text. 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. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Jun 3, 2024
- Updated
- Jun 12, 2024
- SHA
- 382a07ca
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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. -->
digidaw
This model is a fine-tuned version of indolem/indobertweet-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.8189
- Accuracy: 0.263
- Precision: 0.2245
- Recall: 0.2050
- F1: 0.1500
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.9065 | 1.0 | 156 | 3.2812 | 0.283 | 0.2470 | 0.2098 | 0.1605 |
| 0.5336 | 2.0 | 312 | 3.5014 | 0.269 | 0.2350 | 0.2056 | 0.1543 |
| 0.3071 | 3.0 | 468 | 3.8189 | 0.263 | 0.2245 | 0.2050 | 0.1500 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jun 3, 2024
- Updated
- Jun 12, 2024