---
language: en
tags:
- disfluency-detection
- token-classification
- modernbert
- speech-pathology
datasets:
- arielcerdap/disfluency-fluencybank
---

# ModernBERT-large Disfluency — Exp E (Real + RV Oversample x2)

Fine-tuned from [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large).
Train set = real data with RV-containing segments oversampled 2x.
No synthetic data. Val/Test identical to all experiments.

## Oversample stats
- Train original : 2737 segments
- RV segments    : 348 (duplicated 1 extra time(s))
- Train final    : 3085 segments
- RV tokens after: 1858 (4.21%)

## Comparison Table
| Label | Paper | Exp A (base) | Exp C (large) | Exp D (large+mix) | Exp E (large+oversample) |
|---|---|---|---|---|---|
| FP | 1.000 | 0.9944 | 0.9944 | 0.9944 | 0.9915 |
| RP | 0.690 | 0.8022 | 0.8964 | 0.7253 | 0.8802 |
| RV | 0.400 | 0.3145 | 0.4974 | 0.3410 | 0.4884 |
| PW | 0.830 | 0.8879 | 0.9451 | 0.9348 | 0.9409 |
| Macro | 0.730 | 0.7497 | 0.8333 | 0.7489 | 0.8253 |
| Binary F1 | — | 0.8902 | 0.9250 | 0.8459 | 0.9344 |

## Per-class Detail
| Label | P | R | F1 | Support |
|---|---|---|---|---|
| O | 0.9895 | 0.9881 | 0.9888 | 3704 |
| FP | 0.9832 | 1.0000 | 0.9915 | 176 |
| RP | 0.8541 | 0.9080 | 0.8802 | 174 |
| RV | 0.4884 | 0.4884 | 0.4884 | 86 |
| PW | 0.9598 | 0.9227 | 0.9409 | 233 |


## Hyperparameters
- learning_rate: 5e-05
- batch_size effective: 32 (8 × 4 grad_accum)
- epochs: 15
- warmup_steps: 97
- weight_decay: 0.1
- classifier_dropout: 0.3
- focal_loss_gamma: 3.0 (adaptive)
- class_weights: O=1.0, FP=3.0, RP=6.0, RV=12.0, PW=5.0
- oversample_factor: 2x RV segments