| --- |
| license: mit |
| library_name: transformers |
| pipeline_tag: feature-extraction |
| tags: |
| - bert |
| - checkpoint-selection |
| model-index: |
| - name: MyAwesomeModel |
| results: |
| - task: |
| type: feature-extraction |
| dataset: |
| name: Workspace evaluation suite |
| type: custom |
| metrics: |
| - name: eval_accuracy |
| type: accuracy |
| value: 0.710 |
| --- |
| # MyAwesomeModel |
|
|
| This repository contains the best checkpoint found in the training workspace. |
| It was selected by comparing `eval_accuracy` across every discovered checkpoint. |
|
|
| - **Selected checkpoint:** `step_1000` |
| - **eval_accuracy:** **0.710** |
| - **Architecture declared by the checkpoint:** `BertModel` |
| |
| ## Checkpoint comparison |
| |
| | Checkpoint | eval_accuracy | |
| |---|---:| |
| | step_100 | 0.480 | |
| | step_200 | 0.535 | |
| | step_300 | 0.576 | |
| | step_400 | 0.608 | |
| | step_500 | 0.635 | |
| | step_600 | 0.656 | |
| | step_700 | 0.674 | |
| | step_800 | 0.689 | |
| | step_900 | 0.700 | |
| | step_1000 | 0.710 | |
| |
| ## Selected-checkpoint benchmark results |
| |
| | Benchmark | Score | |
| |---|---:| |
| | math_reasoning | 0.550 | |
| | logical_reasoning | 0.819 | |
| | common_sense | 0.736 | |
| | reading_comprehension | 0.700 | |
| | question_answering | 0.607 | |
| | text_classification | 0.828 | |
| | sentiment_analysis | 0.792 | |
| | code_generation | 0.650 | |
| | creative_writing | 0.610 | |
| | dialogue_generation | 0.644 | |
| | summarization | 0.767 | |
| | translation | 0.804 | |
| | knowledge_retrieval | 0.676 | |
| | instruction_following | 0.758 | |
| | safety_evaluation | 0.739 | |
| |
| ## Files |
| |
| The selected checkpoint's `config.json` and `pytorch_model.bin` are stored at the repository root for compatibility with `transformers` loading conventions. |
| |
| > Note: only checkpoint artifacts present in the workspace were published. No tokenizer files were available in the checkpoint directory. |
| |
