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test_trainer
yasamingol/test_trainer
test_trainer is a text classification model from yasamingol. 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. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jun 23, 2023
- Updated
- Jun 23, 2023
- SHA
- d47b543b
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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. -->
test_trainer
This model is a fine-tuned version of HooshvareLab/bert-base-parsbert-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4347
- Accuracy: {'accuracy': 0.8962962962962963}
- F1 Weighted: {'f1': 0.8943267815916415}
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 | F1 Weighted |
|---|---|---|---|---|---|
| No log | 1.0 | 270 | 0.4668 | {'accuracy': 0.8851851851851852} | {'f1': 0.8812450190293216} |
| 0.6057 | 2.0 | 540 | 0.4347 | {'accuracy': 0.8962962962962963} | {'f1': 0.8943267815916415} |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Jun 23, 2023
- Updated
- Jun 23, 2023