Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use tkuye/binary-skills-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tkuye/binary-skills-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tkuye/binary-skills-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tkuye/binary-skills-classifier") model = AutoModelForSequenceClassification.from_pretrained("tkuye/binary-skills-classifier") - Notebooks
- Google Colab
- Kaggle
Tosin Kuye commited on
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Parent(s): 55ddf9f
update model card README.md
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README.md
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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### Framework versions
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1373
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- Accuracy: 0.9702
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| 0.098 | 1.0 | 1557 | 0.0917 | 0.9663 |
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| 0.0678 | 2.0 | 3114 | 0.0982 | 0.9712 |
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| 0.0344 | 3.0 | 4671 | 0.1140 | 0.9712 |
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| 0.0239 | 4.0 | 6228 | 0.1373 | 0.9702 |
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### Framework versions
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