KoELECTRA-small-v3-modu-ner
This model is a fine-tuned version of monologg/koelectra-small-v3-discriminator on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1431 - Precision: 0.8232 - Recall: 0.8449 - F1: 0.8339 - Accuracy: 0.9628
Params
10 M
Context
512
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Likes
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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 | 0.1 GB | 0.6 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
- ElectraForTokenClassification
- Parameters
- 10 M
- Tensor type
- F32
- Context length
- 512
- Vocabulary
- 35,000
- Layers / heads
- 12 / 4
- First seen on the Hub
- 2023-03-29
- Training datasets
- undisclosed
- Added to our catalog
- 2026-08-16
Compare with any token-classification model