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213DSA12EW/bert-base-uncased-step1000-best
bert-base-uncased-step1000-best is a machine learning model from 213DSA12EW. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
This model checkpoint (step1000) was selected as the best performing model based on evaluation accuracy across all benchmark categories.
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From the Hugging Face model README
This model checkpoint (step_1000) was selected as the best performing model based on evaluation accuracy across all benchmark categories.
Detailed evaluation scores across all 15 benchmark categories (scores rounded to 3 decimal places):
| Benchmark Category | Score | Weight | Weighted Score |
|---|---|---|---|
| code_generation | 0.769 | 1.1 | 0.846 |
| common_sense | 0.794 | 1.0 | 0.794 |
| creative_writing | 0.729 | 0.9 | 0.656 |
| dialogue_generation | 0.745 | 1.0 | 0.745 |
| instruction_following | 0.818 | 1.1 | 0.9 |
| knowledge_retrieval | 0.834 | 1.0 | 0.834 |
| logical_reasoning | 0.81 | 1.2 | 0.972 |
| math_reasoning | 0.81 | 1.2 | 0.972 |
| question_answering | 0.851 | 1.1 | 0.936 |
| reading_comprehension | 0.826 | 1.0 | 0.826 |
| safety_evaluation | 0.802 | 1.1 | 0.882 |
| sentiment_analysis | 0.891 | 0.9 | 0.802 |
| summarization | 0.761 | 1.0 | 0.761 |
| text_classification | 0.875 | 0.9 | 0.787 |
| translation | 0.778 | 1.0 | 0.778 |
This checkpoint was selected as the best model because it achieved the highest evaluation accuracy among all checkpoints evaluated (steps 100 through 1000).