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balanced-combined-bert
asparius/balanced-combined-bert
balanced-combined-bert is a text classification model from asparius. 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
- Oct 24, 2022
- Updated
- Oct 24, 2022
- SHA
- 31789437
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. -->
balanced-combined-bert
This model is a fine-tuned version of dbmdz/bert-base-turkish-128k-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4475
- Accuracy: 0.825
- F1: 0.8141
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: 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
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Oct 24, 2022
- Updated
- Oct 24, 2022