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distilbert-base-uncased-finetuned_gender_classification
padmajabfrl/distilbert-base-uncased-finetuned_gender_classification
distilbert-base-uncased-finetuned_gender_classification is a text classification model from padmajabfrl. 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
- distilbert
- Access
- Public
- Created
- Jan 5, 2023
- Updated
- Jan 9, 2023
- SHA
- 58b1b48f
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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. -->
distilbert-base-uncased-finetuned_gender_classification
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.003 | 1.0 | 4390 | 0.0000 | 1.0 |
| 0.0069 | 2.0 | 8780 | 0.0000 | 1.0 |
| 0.0014 | 3.0 | 13170 | 0.0000 | 1.0 |
| 0.0014 | 4.0 | 17560 | 0.0000 | 1.0 |
| 0.0008 | 5.0 | 21950 | 0.0000 | 1.0 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jan 5, 2023
- Updated
- Jan 9, 2023