---
dataset_info:
- config_name: corpus
  features:
  - name: _id
    dtype: string
  - name: title
    dtype: string
  - name: partition
    dtype: string
  - name: text
    dtype: string
  - name: language
    dtype: string
  - name: meta_information
    struct:
    - name: resource
      dtype: string
  splits:
  - name: corpus
    num_bytes: 1556153
    num_examples: 1008
  download_size: 665795
  dataset_size: 1556153
- config_name: default
  features:
  - name: query-id
    dtype: string
  - name: corpus-id
    dtype: string
  - name: score
    dtype: int64
  splits:
  - name: train
    num_bytes: 13644
    num_examples: 561
  - name: valid
    num_bytes: 5413
    num_examples: 226
  - name: test
    num_bytes: 5293
    num_examples: 221
  download_size: 15613
  dataset_size: 24350
- config_name: queries
  features:
  - name: _id
    dtype: string
  - name: title
    dtype: string
  - name: partition
    dtype: string
  - name: text
    dtype: string
  - name: language
    dtype: string
  - name: meta_information
    struct:
    - name: resource
      dtype: string
  splits:
  - name: queries
    num_bytes: 838872
    num_examples: 1008
  download_size: 410063
  dataset_size: 838872
configs:
- config_name: corpus
  data_files:
  - split: corpus
    path: corpus/corpus-*
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: valid
    path: data/valid-*
  - 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)
```