Draft: Single layer classifier evaluator #1385
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Fraser-Greenlee
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Fraser-Greenlee
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Jan 18, 2022
| def test_SingleLayerClassificationEvaluator(self): | ||
| """Tests that the SingleLayerClassificationEvaluator can loads and runs with reasonable performance.""" | ||
| model = SentenceTransformer('paraphrase-distilroberta-base-v1') | ||
| df = pd.read_csv('datasets/ag_news.csv')[:1_000] |
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Taken from https://huggingface.co/datasets/ag_news
Fraser-Greenlee
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Hi! I'm also very interested in creating more evaluator for testing downstream tasks. I tried creating a similar evaluator like yours by using an sklearn single layer perceptron for regression. The score of sklearn MLPRegressor is R2 score, which might not be useful because it sometimes gets a negative result. Do you have a better idea? |
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Resolves: #1380
Uses an sklearn single layer perceptron trained on a set of sentence embeddings and class labels.
The classifier accuracy indicates how good the semantic encoding is.
This could be used to evaluate a semantic encoders performance on a range of classification task while it trains.