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README.md
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datasets:
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- disham993/ElectricalDeviceFeedbackBalanced
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metrics:
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- epoch: 5
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- eval_f1: 0.8899
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- eval_accuracy: 0.8875
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- eval_runtime: 1.2105
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- eval_samples_per_second: 1116.881
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- eval_steps_per_second: 18.174
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---
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# electrical-classification-ModernBERT-base
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
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model_name = "disham993/electrical-classification-ModernBERT-
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForSequenceClassification.from_pretrained(model_name)
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nlp = pipeline("text-classification", model=model, tokenizer=tokenizer)
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## Last update
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2025-01-05
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datasets:
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- disham993/ElectricalDeviceFeedbackBalanced
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metrics:
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- epoch: 5
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- eval_f1: 0.8899
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- eval_accuracy: 0.8875
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- eval_runtime: 1.2105
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- eval_samples_per_second: 1116.881
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- eval_steps_per_second: 18.174
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library_name: transformers
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---
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# electrical-classification-ModernBERT-base
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
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model_name = "disham993/electrical-classification-ModernBERT-base"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForSequenceClassification.from_pretrained(model_name)
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nlp = pipeline("text-classification", model=model, tokenizer=tokenizer)
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## Last update
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2025-01-05
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