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# bert-base-cased-conversational-ner

This model is a fine-tuned version of [DeepPavlov/bert-base-cased-conversational](https://huggingface.co/DeepPavlov/bert-base-cased-conversational) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3583
- Job Title precision: 0.8377
- Job Title recall: 0.8317
- Job Title f1: 0.8347
- Loc precision: 0.8938
- Loc recall: 0.9340
- Loc f1: 0.9135
- Org precision: 0.7092
- Org recall: 0.7032
- Org f1: 0.7062
- Misc precision: 0.6246
- Misc recall: 0.7270
- Misc f1: 0.6719
- Precision: 0.8154
- Recall: 0.8240
- F1: 0.8197
- Accuracy: 0.8687

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Job Title precision | Job Title recall | Job Title f1 | Loc precision | Loc recall | Loc f1 | Org precision | Org recall | Org f1 | Misc precision | Misc recall | Misc f1 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:----------------:|:------------:|:-------------:|:----------:|:------:|:-------------:|:----------:|:------:|:--------------:|:-----------:|:-------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 308  | 0.3583          | 0.8377              | 0.8317           | 0.8347       | 0.8938        | 0.9340     | 0.9135 | 0.7092        | 0.7032     | 0.7062 | 0.6246         | 0.7270      | 0.6719  | 0.8154    | 0.8240 | 0.8197 | 0.8687   |
| 0.3975        | 2.0   | 616  | 0.3767          | 0.7906              | 0.9035           | 0.8433       | 0.8731        | 0.9614     | 0.9151 | 0.6275        | 0.7973     | 0.7023 | 0.6623         | 0.6894      | 0.6756  | 0.7658    | 0.8866 | 0.8218 | 0.8669   |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.7.1+cu110
- Datasets 2.12.0
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-base-cased-conversational-ner", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

bert-base-cased-conversational-ner
==================================


This model is a fine-tuned version of DeepPavlov/bert-base-cased-conversational on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3583
* Job Title precision: 0.8377
* Job Title recall: 0.8317
* Job Title f1: 0.8347
* Loc precision: 0.8938
* Loc recall: 0.9340
* Loc f1: 0.9135
* Org precision: 0.7092
* Org recall: 0.7032
* Org f1: 0.7062
* Misc precision: 0.6246
* Misc recall: 0.7270
* Misc f1: 0.6719
* Precision: 0.8154
* Recall: 0.8240
* F1: 0.8197
* Accuracy: 0.8687


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 1.7.1+cu110
* Datasets 2.12.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.7.1+cu110
* Datasets 2.12.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.7.1+cu110
* Datasets 2.12.0
* Tokenizers 0.13.2