Arunavaonly / text-classification updated 2 years ago

Bangla-twoclass-Sentiment-Analyzer

Name: Bangla-twoclass-Sentiment-Analyzer
Author: Arunavaonly

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.7755 - F1: 0.6113

Params

280 M

Context

512

Downloads 30d

454 K

Likes

Commercial use: allowed mit Not gated SAFETENSORS View on Hugging Face ↗

Download history

daily snapshots · 10 days

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Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	f32	1.1 GB	1.8 GB	✅ Runs comfortably

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Specifications

Architecture: XLMRobertaForSequenceClassification
Parameters: 280 M
Tensor type: F32
Context length: 512
Vocabulary: 250,002
Layers / heads: 12 / 12
Licence: mit
First seen on the Hub: 2023-09-03
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Compare with

bge-reranker-v2-m3 19.2 M finbert 5.6 M bge-reranker-base 4.6 M Prompt-Guard-86M 4.5 M twitter-roberta-base-sentiment-latest 2.6 M bertweet-base-sentiment-analysis 1.5 M

Appears in

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