Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use PracticalWork/distilbert-base-uncased-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PracticalWork/distilbert-base-uncased-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PracticalWork/distilbert-base-uncased-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PracticalWork/distilbert-base-uncased-classifier") model = AutoModelForSequenceClassification.from_pretrained("PracticalWork/distilbert-base-uncased-classifier") - Notebooks
- Google Colab
- Kaggle
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| No log | 1.2013 | 376 | 0.3155 | 0.8761 | 0.7717 |
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| 0.3491 | 1.8019 | 564 | 0.3068 | 0.8833 | 0.7972 |
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| 0.3491 | 2.4026 | 752 | 0.3198 | 0.8833 | 0.8016 |
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### Framework versions
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| No log | 1.2013 | 376 | 0.3155 | 0.8761 | 0.7717 |
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| 0.3491 | 1.8019 | 564 | 0.3068 | 0.8833 | 0.7972 |
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| 0.3491 | 2.4026 | 752 | 0.3198 | 0.8833 | 0.8016 |
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| 0.3491 | 3 | 939 | 0.3165 | 0.8809 | 0.7916 |
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### Framework versions
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