Bangla-twoclass-Sentiment-Analyzer
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
3.4 M
Likes
12
Download history
daily snapshots · 106 days
▲ 2.6 M in the last 30 days (329.0%)
3.4 M887 K
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3.4 M381 K
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3.4 M381 K
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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 any text-classification model