| --- |
| dataset_info: |
| - config_name: corpus |
| features: |
| - name: _id |
| dtype: string |
| - name: partition |
| dtype: string |
| - name: text |
| dtype: string |
| - name: language |
| dtype: string |
| - name: title |
| dtype: string |
| splits: |
| - name: corpus |
| num_bytes: 24718668 |
| num_examples: 19931 |
| download_size: 13352028 |
| dataset_size: 24718668 |
| - config_name: default |
| features: |
| - name: query-id |
| dtype: string |
| - name: corpus-id |
| dtype: string |
| - name: score |
| dtype: int64 |
| splits: |
| - name: train |
| num_bytes: 368416 |
| num_examples: 13951 |
| - name: test |
| num_bytes: 55832 |
| num_examples: 1994 |
| download_size: 182796 |
| dataset_size: 424248 |
| - config_name: queries |
| features: |
| - name: _id |
| dtype: string |
| - name: partition |
| dtype: string |
| - name: text |
| dtype: string |
| - name: language |
| dtype: string |
| - name: title |
| dtype: string |
| splits: |
| - name: queries |
| num_bytes: 28244088 |
| num_examples: 19931 |
| download_size: 14308141 |
| dataset_size: 28244088 |
| configs: |
| - config_name: corpus |
| data_files: |
| - split: corpus |
| path: corpus/corpus-* |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: test |
| path: data/test-* |
| - config_name: queries |
| data_files: |
| - split: queries |
| path: queries/queries-* |
| --- |
| Employing the MTEB evaluation framework's dataset version, utilize the code below for assessment: |
|
|
| ```python |
| import mteb |
| import logging |
| from sentence_transformers import SentenceTransformer |
| from mteb import MTEB |
| |
| logger = logging.getLogger(__name__) |
| |
| model_name = 'intfloat/e5-base-v2' |
| model = SentenceTransformer(model_name) |
| tasks = mteb.get_tasks( |
| tasks=[ |
| "AppsRetrieval", |
| "CodeFeedbackMT", |
| "CodeFeedbackST", |
| "CodeTransOceanContest", |
| "CodeTransOceanDL", |
| "CosQA", |
| "SyntheticText2SQL", |
| "StackOverflowQA", |
| "COIRCodeSearchNetRetrieval", |
| "CodeSearchNetCCRetrieval", |
| ] |
| ) |
| evaluation = MTEB(tasks=tasks) |
| results = evaluation.run( |
| model=model, |
| overwrite_results=True |
| ) |
| print(result) |
| ``` |