Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Definite/klue-bert-cult-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Definite/klue-bert-cult-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Definite/klue-bert-cult-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Definite/klue-bert-cult-classification") model = AutoModelForSequenceClassification.from_pretrained("Definite/klue-bert-cult-classification") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
README.md
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This model is a fine-tuned version of [Definite/klue-bert-mlm-bible](https://huggingface.co/Definite/klue-bert-mlm-bible) 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: 1.0
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| No log | 1.0 | 313 | 0.0011 | 1.0 |
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### Framework versions
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This model is a fine-tuned version of [Definite/klue-bert-mlm-bible](https://huggingface.co/Definite/klue-bert-mlm-bible) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0006
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- Accuracy: 1.0
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 313 | 0.0011 | 1.0 |
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| 0.0524 | 2.0 | 626 | 0.0006 | 1.0 |
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### Framework versions
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