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liufeng145/MyAwesomeModel-step_1000
MyAwesomeModel-step_1000 is a text classification model from liufeng145. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
This is the best-performing checkoint of MyAwesomeModel, trained for 1000 steps.
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From the Hugging Face model README
This is the best-performing checkoint of MyAwesomeModel, trained for 1000 steps.
MyAwesomeModel is a BERT-based model with improved reasoning and inference capabilities. This checkoint represents the final training step and demonstrates strong performance across multiple benchmark categories.
| Benchmark Category | Score |
|---|---|
| Math Reasoning | 0.550 |
| Logical Reasoning | 0.819 |
| Common Sense | 0.736 |
| Reading Comprehension | 0.700 |
| Question Answering | 0.607 |
| Sentiment Analysis | 0.792 |
| Summarization | 0.767 |
| Translation | 0.804 |
| Knowledge Retrieval | 0.676 |
| Creative Writing | 0.610 |
| Instruction Following | 0.758 |
| Safety Evaluation | 0.739 |
| Checkoint | Overall Score |
|---|---|
| step_1000 | 0.712 |
| step_900 | 0.703 |
| step_800 | 0.691 |
| step_700 | 0.677 |
| step_600 | 0.659 |
| step_500 | 0.638 |
| step_400 | 0.612 |
| step_300 | 0.581 |
| step_200 | 0.544 |
| step_100 | 0.493 |
from transformers import BertModel, AutoTokenizer
model = BertModel.from_pretrained("liufeng145/MyAwesomeModel-step_1000")
tokenizer = AutoTokenizer.from_pretrained("liufeng145/MyAwesomeModel-step_1000")
This model is licensed under the MIT License.