Upload best checkpoint with detailed benchmark README
Browse files- README.md +35 -0
- config.json +4 -0
- pytorch_model.bin +3 -0
README.md
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---
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license: mit
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library_name: transformers
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tags:
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- bert
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- checkpoint
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---
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# MyAwesomeModel Best Checkpoint
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Selected checkpoint: `step_1000`
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Selection metric: highest `eval_accuracy` = `0.828`
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## Detailed Evaluation Results
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All scores are reported to three decimal places.
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| Category | Benchmark | Score |
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|---|---|---:|
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| Core Reasoning Tasks | Math Reasoning | 0.550 |
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| Core Reasoning Tasks | Logical Reasoning | 0.819 |
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| Core Reasoning Tasks | Common Sense | 0.736 |
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| Language Understanding | Reading Comprehension | 0.700 |
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| Language Understanding | Question Answering | 0.607 |
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| Language Understanding | Text Classification | 0.828 |
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| Language Understanding | Sentiment Analysis | 0.792 |
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| Generation Tasks | Code Generation | 0.650 |
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| Generation Tasks | Creative Writing | 0.610 |
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| Generation Tasks | Dialogue Generation | 0.644 |
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| Generation Tasks | Summarization | 0.767 |
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| Specialized Capabilities | Translation | 0.804 |
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| Specialized Capabilities | Knowledge Retrieval | 0.676 |
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| Specialized Capabilities | Instruction Following | 0.758 |
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| Specialized Capabilities | Safety Evaluation | 0.739 |
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config.json
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{
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"model_type": "bert",
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"architectures": ["BertModel"]
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:965362299a238de576a92dfdd3e32aea7a2bacc94b2c41541c8c9258b923f587
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size 23
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