Instructions to use RvKy/bert_FineTuned_MultiClass_news with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RvKy/bert_FineTuned_MultiClass_news with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RvKy/bert_FineTuned_MultiClass_news")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RvKy/bert_FineTuned_MultiClass_news") model = AutoModelForSequenceClassification.from_pretrained("RvKy/bert_FineTuned_MultiClass_news") - Notebooks
- Google Colab
- Kaggle
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* We got the validation skor and follow the metric accuracy. The model gave us successfully result.
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* We got the validation skor and follow the metric accuracy. The model gave us successfully result.
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### Training results
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| Epoch | Train Loss | Validation Loss | accuracy | val_accuracy |
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|:-----:|:----------:|:---------------:|:--------:|:------------:|
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| 0 | 0.739859 | 0.507217 | 0.766797 | 0.828693 |
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| 1 | 0.413323 | 0.474160 | 0.865625 | 0.843466 |
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