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# disfluency-large

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: 0.0438
- Precision: 0.9698
- Recall: 0.9663
- F1: 0.9681
- Accuracy: 0.9921

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 140  | 0.0422          | 0.9651    | 0.9627 | 0.9639 | 0.9902   |
| No log        | 2.0   | 280  | 0.0315          | 0.9718    | 0.9730 | 0.9724 | 0.9923   |
| No log        | 3.0   | 420  | 0.2221          | 0.8079    | 0.7530 | 0.7795 | 0.9355   |
| 0.024         | 4.0   | 560  | 0.0379          | 0.9693    | 0.9675 | 0.9684 | 0.9926   |
| 0.024         | 5.0   | 700  | 0.0499          | 0.9657    | 0.9639 | 0.9648 | 0.9905   |
| 0.024         | 6.0   | 840  | 0.0388          | 0.9688    | 0.9688 | 0.9688 | 0.9925   |
| 0.024         | 7.0   | 980  | 0.0438          | 0.9698    | 0.9663 | 0.9681 | 0.9921   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "disfluency-large", "results": []}]}
transformers pytorch tensorboard roberta token-classification generated_from_trainer autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #has_space #region-us 

disfluency-large
================


This model is a fine-tuned version of vinai/phobert-large on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0438
* Precision: 0.9698
* Recall: 0.9663
* F1: 0.9681
* Accuracy: 0.9921


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: 15


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### 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: 15 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### 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: 15 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #has_space #region-us 
### 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: 15### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3