experiment with different models
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experiment with different models is Iterate over a list of models and determine which one performs the best.
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| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Action | [1] |
| Rdf:type | Testing Operation | [3] |
| Part of | Refine Models | [1] |
| Method for | Refine Models | [1] |
| Is Suggested by | Next Steps | [2] |
| Description | Iterate over a list of models and determine which one performs the best | [3] |
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ctx:claims/beam/fe5b22b9-de5a-42a8-ae33-5d8f47d014d6- full textbeam-chunktext/plain1 KB
doc:beam/fe5b22b9-de5a-42a8-ae33-5d8f47d014d6Show excerpt
- The `compute_metrics` function computes accuracy and F1-score using Scikit-learn's `accuracy_score` and `f1_score`. 2. **Collect Data**: - We use `make_classification` to generate synthetic data for demonstration purposes. In a rea…
ctx:claims/beam/0e4dede6-52a5-49ce-a450-4813d1738359- full textbeam-chunktext/plain990 B
doc:beam/0e4dede6-52a5-49ce-a450-4813d1738359Show excerpt
- Load and split the dataset into training and testing sets. - Tokenize the data using the tokenizer. 2. **Model Fine-Tuning**: - Define a custom dataset class to handle the tokenized data. - Set up training arguments and defin…
ctx:claims/beam/b1c13f74-d586-4364-a78a-3777454bef7f- full textbeam-chunktext/plain1 KB
doc:beam/b1c13f74-d586-4364-a78a-3777454bef7fShow excerpt
"distilbert-base-uncased" ] # Experiment with different models best_accuracy = 0 best_model = None for model_name in models_to_test: accuracy = train_and_evaluate_model(model_name, train_df, test_df) if accuracy > best_accuracy…
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