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MyAwesomeModel-step1000
safafaf22/MyAwesomeModel-step1000
MyAwesomeModel-step1000 is a feature extraction model from safafaf22. 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 holds the best checkpoint of MyAwesomeModel, selected from the workspace training run (checkpoints/step1000). The selection was made by running the workspace's own evaluation/eval.py pipeline across al…
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At a glance
- Task
- Feature Extraction
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Sep 5, 2026
- Updated
- Sep 5, 2026
- SHA
- 3cbb8460
Model card
From the Hugging Face model README
MyAwesomeModel (step_1000)
This repository holds the best checkpoint of MyAwesomeModel, selected from the
workspace training run (checkpoints/step_1000). The selection was made by running
the workspace's own evaluation/eval.py pipeline across all 10 checkpoints
(step_100 … step_1000); step_1000 achieved the highest weighted overall score.
Selected checkpoint
- Checkpoint:
step_1000 - Weighted overall score:
0.712(highest among all checkpoints)
Evaluation results — all 15 benchmarks (step_1000)
Scores are reported to 3 decimal places.
| # | Benchmark | Score |
|---|---|---|
| 1 | math_reasoning | 0.550 |
| 2 | code_generation | 0.650 |
| 3 | text_classification | 0.828 |
| 4 | sentiment_analysis | 0.792 |
| 5 | question_answering | 0.607 |
| 6 | logical_reasoning | 0.819 |
| 7 | common_sense | 0.736 |
| 8 | reading_comprehension | 0.700 |
| 9 | dialogue_generation | 0.644 |
| 10 | summarization | 0.767 |
| 11 | translation | 0.804 |
| 12 | knowledge_retrieval | 0.676 |
| 13 | creative_writing | 0.610 |
| 14 | instruction_following | 0.758 |
| 15 | safety_evaluation | 0.739 |
Weighted overall score
The overall score is the weighted average of the 15 benchmark scores, using the
weights defined in evaluation/eval.py (reasoning tasks receive extra weight):
- math_reasoning ×1.2, logical_reasoning ×1.2
- code_generation ×1.1, question_answering ×1.1, instruction_following ×1.1, safety_evaluation ×1.1
- reading_comprehension ×1.0, common_sense ×1.0, dialogue_generation ×1.0, summarization ×1.0, translation ×1.0, knowledge_retrieval ×1.0
- text_classification ×0.9, sentiment_analysis ×0.9, creative_writing ×0.9
Weighted overall = 0.712.
- Task
- Feature Extraction
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Sep 5, 2026
- Updated
- Sep 5, 2026