Instructions to use sdfaffaf556/my-awesome-model-best with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sdfaffaf556/my-awesome-model-best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sdfaffaf556/my-awesome-model-best")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sdfaffaf556/my-awesome-model-best") model = AutoModel.from_pretrained("sdfaffaf556/my-awesome-model-best", device_map="auto") - Notebooks
- Google Colab
- Kaggle
MyAwesomeModel - Best Checkpoint (step_1000)
This is the best performing checkpoint of MyAwesomeModel, selected from 10 training checkpoints (step_100 through step_1000) based on comprehensive benchmark evaluation.
Evaluation Results
The model was evaluated across 15 benchmark categories. Results for the best checkpoint (step_1000):
| Benchmark | Score |
|---|---|
| math_reasoning | 0.550 |
| code_generation | 0.650 |
| text_classification | 0.828 |
| sentiment_analysis | 0.792 |
| question_answering | 0.607 |
| logical_reasoning | 0.819 |
| common_sense | 0.736 |
| reading_comprehension | 0.700 |
| dialogue_generation | 0.644 |
| summarization | 0.767 |
| translation | 0.804 |
| knowledge_retrieval | 0.676 |
| creative_writing | 0.610 |
| instruction_following | 0.758 |
| safety_evaluation | 0.739 |
Overall Weighted Score: 0.710
Selection Methodology
The best checkpoint was selected by evaluating all 10 checkpoints across all 15 benchmarks using a weighted scoring system:
- Reasoning tasks (math_reasoning, logical_reasoning) receive higher weight (1.2)
- Code generation, question answering, instruction following, and safety evaluation receive weight (1.1)
- Other tasks receive weight (1.0) or (0.9)
All training curves show monotonic improvement, with step_1000 achieving the highest overall score.
Usage
Load the model:
from transformers import AutoModel, AutoConfig
model = AutoModel.from_pretrained("sdfaffaf556/my-awesome-model-best")
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