Text Classification
Transformers
ONNX
Safetensors
English
Tagalog
xlm-roberta
sentiment-analysis
filipino
taglish
text-embeddings-inference
Instructions to use cjcastro/xlm-roberta-Rise-On-AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cjcastro/xlm-roberta-Rise-On-AI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cjcastro/xlm-roberta-Rise-On-AI")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cjcastro/xlm-roberta-Rise-On-AI") model = AutoModelForSequenceClassification.from_pretrained("cjcastro/xlm-roberta-Rise-On-AI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload training_config.json with huggingface_hub
Browse files- training_config.json +1 -1
training_config.json
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"early_stopping_patience": 5,
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"hp_trials": 1,
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"output_dir": "C:\\xampp\\htdocs\\Rise-On-AI\\scripts\\sentiment-model-training\\outputs\\best_model",
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"best_eval_f1_macro": 0.
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}
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"early_stopping_patience": 5,
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"hp_trials": 1,
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"output_dir": "C:\\xampp\\htdocs\\Rise-On-AI\\scripts\\sentiment-model-training\\outputs\\best_model",
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"best_eval_f1_macro": 0.8157473649436856
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}
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