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---
base_model: vinai/phobert-base
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-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 42.3155
- Precision: 0.9886
- Recall: 0.9862
- F1: 0.9874
- Accuracy: 0.9956

## 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: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 140   | 131.9614        | 0.8037    | 0.8438 | 0.8232 | 0.9411   |
| No log        | 2.0   | 280   | 41.8031         | 0.9487    | 0.9549 | 0.9518 | 0.9855   |
| No log        | 3.0   | 420   | 27.3502         | 0.9664    | 0.9681 | 0.9673 | 0.9906   |
| 178.6738      | 4.0   | 560   | 22.9255         | 0.9741    | 0.9730 | 0.9735 | 0.9925   |
| 178.6738      | 5.0   | 700   | 25.3163         | 0.9676    | 0.9688 | 0.9682 | 0.9919   |
| 178.6738      | 6.0   | 840   | 24.1142         | 0.9723    | 0.9718 | 0.9720 | 0.9925   |
| 178.6738      | 7.0   | 980   | 22.2517         | 0.9777    | 0.9766 | 0.9771 | 0.9938   |
| 25.7318       | 8.0   | 1120  | 24.4542         | 0.9760    | 0.9772 | 0.9766 | 0.9936   |
| 25.7318       | 9.0   | 1260  | 27.1333         | 0.9740    | 0.9700 | 0.9720 | 0.9929   |
| 25.7318       | 10.0  | 1400  | 24.5889         | 0.9789    | 0.9778 | 0.9784 | 0.9938   |
| 16.0059       | 11.0  | 1540  | 26.1038         | 0.9819    | 0.9808 | 0.9814 | 0.9936   |
| 16.0059       | 12.0  | 1680  | 23.3198         | 0.9790    | 0.9814 | 0.9802 | 0.9941   |
| 16.0059       | 13.0  | 1820  | 30.8831         | 0.9778    | 0.9772 | 0.9775 | 0.9930   |
| 16.0059       | 14.0  | 1960  | 28.1502         | 0.9843    | 0.9814 | 0.9828 | 0.9946   |
| 11.2302       | 15.0  | 2100  | 29.2842         | 0.9790    | 0.9808 | 0.9799 | 0.9937   |
| 11.2302       | 16.0  | 2240  | 28.5446         | 0.9819    | 0.9796 | 0.9807 | 0.9945   |
| 11.2302       | 17.0  | 2380  | 25.4603         | 0.9850    | 0.9838 | 0.9844 | 0.9953   |
| 8.9848        | 18.0  | 2520  | 29.3936         | 0.9801    | 0.9760 | 0.9780 | 0.9929   |
| 8.9848        | 19.0  | 2660  | 31.2320         | 0.9796    | 0.9796 | 0.9796 | 0.9944   |
| 8.9848        | 20.0  | 2800  | 34.0474         | 0.9849    | 0.9802 | 0.9825 | 0.9943   |
| 8.9848        | 21.0  | 2940  | 32.9968         | 0.9849    | 0.9826 | 0.9838 | 0.9948   |
| 8.2401        | 22.0  | 3080  | 39.6873         | 0.9819    | 0.9808 | 0.9814 | 0.9946   |
| 8.2401        | 23.0  | 3220  | 42.7506         | 0.9819    | 0.9802 | 0.9811 | 0.9945   |
| 8.2401        | 24.0  | 3360  | 33.8886         | 0.9856    | 0.9862 | 0.9859 | 0.9954   |
| 7.099         | 25.0  | 3500  | 36.8275         | 0.9819    | 0.9808 | 0.9814 | 0.9941   |
| 7.099         | 26.0  | 3640  | 36.7838         | 0.9831    | 0.9814 | 0.9823 | 0.9951   |
| 7.099         | 27.0  | 3780  | 39.2226         | 0.9813    | 0.9790 | 0.9801 | 0.9947   |
| 7.099         | 28.0  | 3920  | 39.2492         | 0.9843    | 0.9820 | 0.9832 | 0.9949   |
| 5.6646        | 29.0  | 4060  | 41.4139         | 0.9790    | 0.9790 | 0.9790 | 0.9944   |
| 5.6646        | 30.0  | 4200  | 41.4583         | 0.9838    | 0.9826 | 0.9832 | 0.9949   |
| 5.6646        | 31.0  | 4340  | 47.1872         | 0.9801    | 0.9778 | 0.9789 | 0.9941   |
| 5.6646        | 32.0  | 4480  | 41.3073         | 0.9862    | 0.9844 | 0.9853 | 0.9956   |
| 5.304         | 33.0  | 4620  | 44.8882         | 0.9796    | 0.9790 | 0.9793 | 0.9945   |
| 5.304         | 34.0  | 4760  | 52.3203         | 0.9783    | 0.9772 | 0.9778 | 0.9941   |
| 5.304         | 35.0  | 4900  | 43.9140         | 0.9825    | 0.9808 | 0.9817 | 0.9951   |
| 4.7574        | 36.0  | 5040  | 46.8215         | 0.9819    | 0.9802 | 0.9811 | 0.9947   |
| 4.7574        | 37.0  | 5180  | 39.5738         | 0.9867    | 0.9844 | 0.9856 | 0.9959   |
| 4.7574        | 38.0  | 5320  | 39.9370         | 0.9837    | 0.9814 | 0.9826 | 0.9955   |
| 4.7574        | 39.0  | 5460  | 40.4614         | 0.9856    | 0.9844 | 0.9850 | 0.9956   |
| 3.8125        | 40.0  | 5600  | 38.6418         | 0.9885    | 0.9850 | 0.9868 | 0.9959   |
| 3.8125        | 41.0  | 5740  | 42.7438         | 0.9813    | 0.9796 | 0.9805 | 0.9947   |
| 3.8125        | 42.0  | 5880  | 52.7676         | 0.9689    | 0.9730 | 0.9709 | 0.9940   |
| 3.2902        | 43.0  | 6020  | 38.5737         | 0.9825    | 0.9808 | 0.9817 | 0.9953   |
| 3.2902        | 44.0  | 6160  | 42.4615         | 0.9868    | 0.9850 | 0.9859 | 0.9952   |
| 3.2902        | 45.0  | 6300  | 43.5099         | 0.9856    | 0.9838 | 0.9847 | 0.9956   |
| 3.2902        | 46.0  | 6440  | 45.0846         | 0.9837    | 0.9820 | 0.9829 | 0.9952   |
| 4.0467        | 47.0  | 6580  | 41.7571         | 0.9862    | 0.9850 | 0.9856 | 0.9955   |
| 4.0467        | 48.0  | 6720  | 50.8592         | 0.9807    | 0.9778 | 0.9792 | 0.9945   |
| 4.0467        | 49.0  | 6860  | 42.3155         | 0.9886    | 0.9862 | 0.9874 | 0.9956   |
| 2.3503        | 50.0  | 7000  | 45.7602         | 0.9873    | 0.9850 | 0.9862 | 0.9952   |
| 2.3503        | 51.0  | 7140  | 43.4314         | 0.9856    | 0.9838 | 0.9847 | 0.9953   |
| 2.3503        | 52.0  | 7280  | 47.4167         | 0.9813    | 0.9790 | 0.9801 | 0.9949   |
| 2.3503        | 53.0  | 7420  | 46.8868         | 0.9838    | 0.9826 | 0.9832 | 0.9952   |
| 2.841         | 54.0  | 7560  | 50.8428         | 0.9843    | 0.9814 | 0.9828 | 0.9950   |
| 2.841         | 55.0  | 7700  | 49.0097         | 0.9825    | 0.9808 | 0.9817 | 0.9949   |
| 2.841         | 56.0  | 7840  | 49.0165         | 0.9831    | 0.9802 | 0.9816 | 0.9950   |
| 2.841         | 57.0  | 7980  | 46.3213         | 0.9838    | 0.9826 | 0.9832 | 0.9953   |
| 1.8064        | 58.0  | 8120  | 49.3268         | 0.9825    | 0.9790 | 0.9807 | 0.9946   |
| 1.8064        | 59.0  | 8260  | 48.1988         | 0.9849    | 0.9814 | 0.9831 | 0.9952   |
| 1.8064        | 60.0  | 8400  | 46.5527         | 0.9838    | 0.9826 | 0.9832 | 0.9955   |
| 1.5941        | 61.0  | 8540  | 57.5747         | 0.9807    | 0.9790 | 0.9798 | 0.9942   |
| 1.5941        | 62.0  | 8680  | 56.6894         | 0.9801    | 0.9790 | 0.9796 | 0.9945   |
| 1.5941        | 63.0  | 8820  | 58.1243         | 0.9808    | 0.9802 | 0.9805 | 0.9945   |
| 1.5941        | 64.0  | 8960  | 53.2165         | 0.9837    | 0.9808 | 0.9822 | 0.9951   |
| 1.5057        | 65.0  | 9100  | 52.2484         | 0.9832    | 0.9820 | 0.9826 | 0.9949   |
| 1.5057        | 66.0  | 9240  | 49.2435         | 0.9837    | 0.9814 | 0.9826 | 0.9951   |
| 1.5057        | 67.0  | 9380  | 51.2186         | 0.9796    | 0.9790 | 0.9793 | 0.9948   |
| 1.5084        | 68.0  | 9520  | 54.1799         | 0.9825    | 0.9808 | 0.9817 | 0.9947   |
| 1.5084        | 69.0  | 9660  | 56.3696         | 0.9807    | 0.9778 | 0.9792 | 0.9945   |
| 1.5084        | 70.0  | 9800  | 52.6295         | 0.9837    | 0.9802 | 0.9819 | 0.9948   |
| 1.5084        | 71.0  | 9940  | 51.2577         | 0.9825    | 0.9790 | 0.9807 | 0.9950   |
| 1.0448        | 72.0  | 10080 | 56.0093         | 0.9807    | 0.9790 | 0.9798 | 0.9945   |
| 1.0448        | 73.0  | 10220 | 50.7540         | 0.9831    | 0.9808 | 0.9819 | 0.9951   |
| 1.0448        | 74.0  | 10360 | 52.9783         | 0.9819    | 0.9790 | 0.9804 | 0.9947   |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3