lschlessinger
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README.md
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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## Training procedure
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### Training results
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### Framework versions
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## Model description
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See the [bert-base-uncased](https://huggingface.co/bert-base-uncased) for more details. The only architectural modification made was to the classification head. Here, 7 classes were used.
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## Intended uses & limitations
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This model is intended for demonstration purposes only. The problem type data was in English and contains many LaTeX tokens.
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## Training and evaluation data
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The `problem` field of [competition_math dataset](https://huggingface.co/datasets/competition_math) was used for training and evaluation input data. The target data was taken from the `type` field.
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## Training procedure
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### Training results
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This fine-tuned model achieves the following result on the problem type competition math test set:
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```
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precision recall f1-score support
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Algebra 0.78 0.79 0.79 1187
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Counting & Probability 0.75 0.81 0.78 474
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Geometry 0.76 0.83 0.79 479
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Intermediate Algebra 0.86 0.84 0.85 903
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Number Theory 0.79 0.82 0.80 540
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Prealgebra 0.66 0.61 0.63 871
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Precalculus 0.95 0.89 0.92 546
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accuracy 0.79 5000
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macro avg 0.79 0.80 0.79 5000
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weighted avg 0.79 0.79 0.79 5000
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```
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### Framework versions
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