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---
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
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