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--- |
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library_name: transformers |
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tags: |
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- text-classification |
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- modernbert |
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- generated-data |
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base_model: illuin/roberta-large-bne |
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metrics: |
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- name: loss |
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type: loss |
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value: 0.46496206521987915 |
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- name: accuracy |
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type: accuracy |
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value: 0.8856666666666667 |
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- name: f1 |
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type: f1 |
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value: 0.8856143611327717 |
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- name: precision |
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type: precision |
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value: 0.8855866997834395 |
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- name: recall |
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type: recall |
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value: 0.8856544163260209 |
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- name: runtime |
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type: runtime |
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value: 10.4045 |
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- name: samples_per_second |
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type: samples_per_second |
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value: 576.672 |
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- name: steps_per_second |
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type: steps_per_second |
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value: 36.042 |
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- name: epoch |
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type: epoch |
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value: 3.0 |
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--- |
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# Gender Classifier (Fine-tuned illuin/roberta-large-bne) |
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This model was fine-tuned to classify text into: male, female, neutral |
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## Performance Metrics |
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| Metric | Value | |
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| :--- | :--- | |
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| **loss** | 0.4650 | |
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| **accuracy** | 0.8857 | |
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| **f1** | 0.8856 | |
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| **precision** | 0.8856 | |
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| **recall** | 0.8857 | |
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| **runtime** | 10.4045 | |
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| **samples_per_second** | 576.6720 | |
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| **steps_per_second** | 36.0420 | |
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| **epoch** | 3.0000 | |
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## Hyperparameters |
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- **Batch Size**: 16 |
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- **Learning Rate**: 5e-05 |
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- **Epochs**: 3 |
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- **Weight Decay**: 0.01 |
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- **Mixed Precision (FP16)**: True |
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## Quick Usage |
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```python |
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from transformers import pipeline |
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# Load the model directly from this folder or HF Hub |
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classifier = pipeline('text-classification', model='.') |
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print(classifier('She is a great engineer.')) |
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``` |
