---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: modernbert-disfluency
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# modernbert-disfluency

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1619
- Precision: 0.8263
- Recall: 0.7602
- F1: 0.7919
- Accuracy: 0.9556

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 4e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 49   | 0.3026          | 0.8905    | 0.5    | 0.6404 | 0.9178   |
| No log        | 2.0   | 98   | 0.2426          | 0.8512    | 0.5861 | 0.6942 | 0.9340   |
| 0.4156        | 3.0   | 147  | 0.1860          | 0.8020    | 0.6721 | 0.7313 | 0.9464   |
| 0.4156        | 4.0   | 196  | 0.1633          | 0.8263    | 0.7602 | 0.7919 | 0.9556   |
| 0.1117        | 5.0   | 245  | 0.1810          | 0.8025    | 0.7992 | 0.8008 | 0.9554   |
| 0.1117        | 6.0   | 294  | 0.1832          | 0.782     | 0.8012 | 0.7915 | 0.9561   |
| 0.0401        | 7.0   | 343  | 0.1956          | 0.8043    | 0.7746 | 0.7891 | 0.9554   |
| 0.0401        | 8.0   | 392  | 0.1973          | 0.7864    | 0.7848 | 0.7856 | 0.9563   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0