Hes-Shenaas-v0.1

Hes Shenaas v0.1

Hes Shenaas v0.1 is a single-model Persian emotion classifier based on XLM-RoBERTa Large. It predicts one of seven labels:

Evaluation

The checkpoint was selected using a fixed 1,232-example validation split. The protected 1,151-example test split was evaluated after checkpoint selection.

Test F1 by class:

These numbers describe the project's frozen Persian emotion benchmark and should not be assumed to transfer unchanged to other domains.

Usage

from transformers import pipeline

classifier = pipeline(
    "text-classification",
    model="Reza2kn/Hes-Shenaas-v0.1",
    tokenizer="Reza2kn/Hes-Shenaas-v0.1",
)

print(classifier("امروز واقعاً روز فوق‌العاده‌ای بود"))

For complete class probabilities:

print(classifier("از این وضعیت خیلی عصبانی‌ام", top_k=None))

The model truncates inputs to 128 tokens, matching training and evaluation.

Training

• Base model: FacebookAI/xlm-roberta-large
• Base revision: c23d21b0620b635a76227c604d44e43a9f0ee389
• Training rows: 8,471
• Original cleaned rows: 4,862
• Added public Persian tweets: 3,609
• Added rows were accepted only when two Gemini 3.8 Flash passes agreed and both marked the text self-contained, natural Persian, supported by exact textual evidence, and at least 0.85 confidence.
• Gemini labels were used for training only. Validation and test texts were excluded from API payloads.
• Selection: maximum validation accuracy with earlier epoch retained on ties
• Selected epoch: 5

Limitations

The model is intended for research and product prototyping, especially short informal Persian text. Emotion labels are subjective, and performance can vary on formal writing, code-switching, sarcasm, dialects, long documents, or domains unlike the evaluation data. The OTHER label combines neutral and ambiguous cases. Do not use predictions as the sole basis for high-impact decisions about people.

Integrity

The published model.safetensors SHA-256 is:

43737d1933dd36966f541e9155aa02be1d394ff9f7ff2e475515fc9ed1413030

The metrics and checkpoint were independently rechecked before release.

Licensing and attribution

The Reza2kn fine-tuning modifications are released under the Apache License, Version 2.0. The underlying XLM-RoBERTa Large model remains subject to its MIT license. Both notices apply to this distribution. See LICENSE. Existing third-party copyright, license, and attribution notices remain applicable.

• Upstream: FacebookAI/xlm-roberta-large; declared license: mit.
  • Retained notice: LICENSE-MIT.