Datasets:

atulkrs
/

mlops-devops-sentiment

language:
  - en
license: apache-2.0
task_categories:
  - text-classification
task_ids:
  - sentiment-analysis
tags:
  - mlops
  - devops
  - sentiment
  - domain-specific
size_categories:
  - n<1K

MLOps & DevOps Sentiment Dataset

Dataset description

A domain-specific sentiment dataset containing real-world MLOps and DevOps scenarios labeled as POSITIVE or NEGATIVE. Built to fine-tune sentiment classifiers for technical operations contexts where general-purpose models (trained on movie reviews) underperform.

Why this dataset exists

General sentiment models misclassify technical sentences. For example:

"The pipeline failed silently" → general models often miss the negativity
"Terraform rollback was effortless" → domain context needed for high confidence

Dataset structure

Split	Examples
Train	24
Test	6

Fields

text — sentence describing an MLOps/DevOps scenario
label — 0 (NEGATIVE) or 1 (POSITIVE)
domain — mlops or devops
text_length — word count (added during preprocessing)

Source

Manually curated by @atulkrs based on real-world MLOps and DevOps engineering experience.

Usage

```python from datasets import load_dataset ds = load_dataset("atulkrs/mlops-devops-sentiment") print(ds["train"][0]) ```

Intended use

Fine-tuning sentiment classifiers for MLOps/DevOps tooling feedback
Benchmarking domain adaptation of general NLP models
Curriculum data for MLOps-aware LLM fine-tuning