Instructions to use SACXZ21DSA23/MyAwesomeModel-best with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SACXZ21DSA23/MyAwesomeModel-best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SACXZ21DSA23/MyAwesomeModel-best")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SACXZ21DSA23/MyAwesomeModel-best") model = AutoModel.from_pretrained("SACXZ21DSA23/MyAwesomeModel-best", device_map="auto") - Notebooks
- Google Colab
- Kaggle
MyAwesomeModel (best checkpoint)
Selected as the best checkpoint from the workspace sweep (checkpoints/step_100 โฆ step_1000).
Selection criterion
- Checkpoint selection is based on the highest eval_accuracy (text-classification accuracy) among the checkpoints in the workspace.
- eval_accuracy by step:
| Step | eval_accuracy |
|---|---|
| 100 | 0.517 |
| 200 | 0.603 |
| 300 | 0.667 |
| 400 | 0.714 |
| 500 | 0.750 |
| 600 | 0.776 |
| 700 | 0.795 |
| 800 | 0.809 |
| 900 | 0.820 |
| 1000 | 0.828 |
- Best checkpoint: step_1000 (highest eval_accuracy = 0.828).
Detailed evaluation results (best checkpoint, step_1000)
All 15 benchmark scores (three decimal places):
| Category | Benchmark | Score |
|---|---|---|
| Core Reasoning | Math Reasoning | 0.550 |
| Core Reasoning | Logical Reasoning | 0.819 |
| Core Reasoning | Common Sense | 0.736 |
| Language Understanding | Reading Comprehension | 0.700 |
| Language Understanding | Question Answering | 0.607 |
| Language Understanding | Text Classification | 0.828 |
| Language Understanding | Sentiment Analysis | 0.792 |
| Generation | Code Generation | 0.650 |
| Generation | Creative Writing | 0.610 |
| Generation | Dialogue Generation | 0.644 |
| Generation | Summarization | 0.767 |
| Specialized | Translation | 0.804 |
| Specialized | Knowledge Retrieval | 0.676 |
| Specialized | Instruction Following | 0.758 |
| Specialized | Safety Evaluation | 0.739 |
- Overall weighted score: 0.710
Files
config.jsonpytorch_model.bin
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