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# roberta_ner_personal_info_v2

This model is a fine-tuned version of [tner/roberta-large-ontonotes5](https://huggingface.co/tner/roberta-large-ontonotes5) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0202
- Precision: 0.9744
- Recall: 0.9803
- F1: 0.9774
- 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: 2e-05
- train_batch_size: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1952        | 1.0   | 621  | 0.0387          | 0.9334    | 0.9414 | 0.9374 | 0.9886   |
| 0.0407        | 2.0   | 1242 | 0.0267          | 0.9587    | 0.9606 | 0.9596 | 0.9923   |
| 0.0246        | 3.0   | 1863 | 0.0230          | 0.9616    | 0.9703 | 0.9660 | 0.9936   |
| 0.0163        | 4.0   | 2484 | 0.0206          | 0.9705    | 0.9730 | 0.9717 | 0.9946   |
| 0.0097        | 5.0   | 3105 | 0.0203          | 0.9702    | 0.9747 | 0.9724 | 0.9946   |
| 0.0076        | 6.0   | 3726 | 0.0194          | 0.9717    | 0.9774 | 0.9746 | 0.9950   |
| 0.0066        | 7.0   | 4347 | 0.0193          | 0.9751    | 0.9780 | 0.9766 | 0.9954   |
| 0.0058        | 8.0   | 4968 | 0.0201          | 0.9720    | 0.9781 | 0.9750 | 0.9952   |
| 0.0044        | 9.0   | 5589 | 0.0222          | 0.9717    | 0.9751 | 0.9734 | 0.9950   |
| 0.0037        | 10.0  | 6210 | 0.0204          | 0.9736    | 0.9786 | 0.9761 | 0.9954   |
| 0.0034        | 11.0  | 6831 | 0.0192          | 0.9771    | 0.9808 | 0.9789 | 0.9958   |
| 0.0028        | 12.0  | 7452 | 0.0210          | 0.9723    | 0.9789 | 0.9756 | 0.9953   |
| 0.0025        | 13.0  | 8073 | 0.0222          | 0.9747    | 0.9792 | 0.9769 | 0.9955   |
| 0.0023        | 14.0  | 8694 | 0.0198          | 0.9771    | 0.9806 | 0.9789 | 0.9958   |
| 0.002         | 15.0  | 9315 | 0.0202          | 0.9744    | 0.9803 | 0.9774 | 0.9956   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "tner/roberta-large-ontonotes5", "model-index": [{"name": "roberta_ner_personal_info_v2", "results": []}]}
transformers pytorch safetensors roberta token-classification generated_from_trainer base_model:tner/roberta-large-ontonotes5 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #safetensors #roberta #token-classification #generated_from_trainer #base_model-tner/roberta-large-ontonotes5 #autotrain_compatible #endpoints_compatible #has_space #region-us 

roberta\_ner\_personal\_info\_v2
================================


This model is a fine-tuned version of tner/roberta-large-ontonotes5 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0202
* Precision: 0.9744
* Recall: 0.9803
* F1: 0.9774
* 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: 2e-05
* train\_batch\_size: 20
* eval\_batch\_size: 20
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 20
* eval\_batch\_size: 20
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #safetensors #roberta #token-classification #generated_from_trainer #base_model-tner/roberta-large-ontonotes5 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 20
* eval\_batch\_size: 20
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3