---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: disfluency-large-3
  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. -->

# disfluency-large-3

This model is a fine-tuned version of [vinai/phobert-large](https://huggingface.co/vinai/phobert-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0364
- Precision: 0.9849
- Recall: 0.9802
- F1: 0.9825
- Accuracy: 0.9936

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 140  | 0.0713          | 0.8955    | 0.9165 | 0.9059 | 0.9816   |
| No log        | 2.0   | 280  | 0.0334          | 0.9706    | 0.9730 | 0.9718 | 0.9925   |
| No log        | 3.0   | 420  | 0.0584          | 0.9656    | 0.9609 | 0.9633 | 0.9880   |
| 0.1335        | 4.0   | 560  | 0.0352          | 0.9742    | 0.9742 | 0.9742 | 0.9922   |
| 0.1335        | 5.0   | 700  | 0.0539          | 0.9651    | 0.9633 | 0.9642 | 0.9894   |
| 0.1335        | 6.0   | 840  | 0.0293          | 0.9730    | 0.9754 | 0.9742 | 0.9924   |
| 0.1335        | 7.0   | 980  | 0.0364          | 0.9849    | 0.9802 | 0.9825 | 0.9936   |
| 0.0146        | 8.0   | 1120 | 0.0343          | 0.9795    | 0.9778 | 0.9786 | 0.9941   |
| 0.0146        | 9.0   | 1260 | 0.0268          | 0.9802    | 0.9814 | 0.9808 | 0.9947   |
| 0.0146        | 10.0  | 1400 | 0.0427          | 0.9682    | 0.9688 | 0.9685 | 0.9918   |
| 0.0076        | 11.0  | 1540 | 0.0429          | 0.9576    | 0.9633 | 0.9605 | 0.9899   |
| 0.0076        | 12.0  | 1680 | 0.0343          | 0.9735    | 0.9730 | 0.9732 | 0.9933   |
| 0.0076        | 13.0  | 1820 | 0.0305          | 0.9801    | 0.9754 | 0.9777 | 0.9939   |
| 0.0076        | 14.0  | 1960 | 0.0437          | 0.9765    | 0.9742 | 0.9753 | 0.9924   |
| 0.0047        | 15.0  | 2100 | 0.0363          | 0.9778    | 0.9778 | 0.9778 | 0.9939   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3