Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use PracticalWork/xlm-roberta-large-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PracticalWork/xlm-roberta-large-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PracticalWork/xlm-roberta-large-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PracticalWork/xlm-roberta-large-classifier") model = AutoModelForSequenceClassification.from_pretrained("PracticalWork/xlm-roberta-large-classifier") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -40,7 +40,7 @@ The following hyperparameters were used during training:
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| No log | 0 | 0 | 0.6059 | 0.7106 | 0.1957 |
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| No log | 0.6006 | 188 | 0.4820 | 0.7826 | 0.6 |
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| No log | 1.2013 | 376 | 0.4764 | 0.7858 | 0.
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| 0.5275 | 1.8019 | 564 | 0.5046 | 0.7738 | 0.6519 |
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| 0.5275 | 2.4026 | 752 | 0.4234 | 0.8233 | 0.7041 |
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| 0.5275 | 3 | 939 | 0.3918 | 0.8353 | 0.7325 |
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| 40 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
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| 41 |
| No log | 0 | 0 | 0.6059 | 0.7106 | 0.1957 |
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| 42 |
| No log | 0.6006 | 188 | 0.4820 | 0.7826 | 0.6 |
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| No log | 1.2013 | 376 | 0.4764 | 0.7858 | 0.5553 |
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| 44 |
| 0.5275 | 1.8019 | 564 | 0.5046 | 0.7738 | 0.6519 |
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| 45 |
| 0.5275 | 2.4026 | 752 | 0.4234 | 0.8233 | 0.7041 |
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| 46 |
| 0.5275 | 3 | 939 | 0.3918 | 0.8353 | 0.7325 |
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