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DSD1231/MyAwesomeModel
MyAwesomeModel is a feature extraction model from DSD1231. Use it when you need embeddings to search or compare text. It is set up for transformers. The card lists the license as mit.
This repository contains the checkpoint selected from the workspace evaluation run.
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From the Hugging Face model README
This repository contains the checkpoint selected from the workspace evaluation run.
step_1000eval_accuracy: 0.710eval_accuracy among step_100 through step_1000The overall score is the weighted average defined by the workspace evaluation driver. Individual benchmark scores are rounded and displayed to exactly three decimal places.
| Category | Benchmark | Weight | Score |
|---|---|---|---|
| Core reasoning | Math Reasoning | 1.200 | 0.550 |
| Core reasoning | Logical Reasoning | 1.200 | 0.819 |
| Core reasoning | Common Sense | 1.000 | 0.736 |
| Language understanding | Reading Comprehension | 1.000 | 0.700 |
| Language understanding | Question Answering | 1.100 | 0.607 |
| Language understanding | Text Classification | 0.900 | 0.828 |
| Language understanding | Sentiment Analysis | 0.900 | 0.792 |
| Generation | Code Generation | 1.100 | 0.650 |
| Generation | Creative Writing | 0.900 | 0.610 |
| Generation | Dialogue Generation | 1.000 | 0.644 |
| Generation | Summarization | 1.000 | 0.767 |
| Specialized capabilities | Translation | 1.000 | 0.804 |
| Specialized capabilities | Knowledge Retrieval | 1.000 | 0.676 |
| Specialized capabilities | Instruction Following | 1.100 | 0.758 |
| Specialized capabilities | Safety Evaluation | 1.100 | 0.739 |
The workspace checkpoint uses a BERT configuration. Its pytorch_model.bin is a 23-byte dummy artifact, identical across the candidate checkpoints, so this repository is an evaluation-workflow artifact rather than a usable trained model.