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gemash
bwahyuh/gemash
gemash 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 27, 2024
- Updated
- Jun 28, 2024
- SHA
- 8b84dce0
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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. -->
gemash
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: 0.9414
- Accuracy: 0.8033
- Precision: 0.8149
- Recall: 0.8086
- F1: 0.8116
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.2534 | 1.0 | 169 | 0.9392 | 0.6333 | 0.6682 | 0.6642 | 0.6550 |
| 0.6263 | 2.0 | 338 | 0.7132 | 0.7767 | 0.8099 | 0.7776 | 0.7901 |
| 0.194 | 3.0 | 507 | 0.8639 | 0.7883 | 0.7911 | 0.8039 | 0.7961 |
| 0.0485 | 4.0 | 676 | 0.9414 | 0.8033 | 0.8149 | 0.8086 | 0.8116 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jun 27, 2024
- Updated
- Jun 28, 2024