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# bert-finetuned-ner

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the wikiann dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5677
- Precision: 0.3452
- Recall: 0.5421
- F1: 0.4218
- Accuracy: 0.8688

## 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 13   | 0.5728          | 0.2077    | 0.3551 | 0.2621 | 0.8199   |
| No log        | 2.0   | 26   | 0.5687          | 0.2889    | 0.3645 | 0.3223 | 0.8312   |
| No log        | 3.0   | 39   | 0.5447          | 0.2857    | 0.4486 | 0.3491 | 0.8425   |
| No log        | 4.0   | 52   | 0.5509          | 0.2881    | 0.4766 | 0.3592 | 0.8489   |
| No log        | 5.0   | 65   | 0.5751          | 0.3121    | 0.4579 | 0.3712 | 0.8511   |
| No log        | 6.0   | 78   | 0.5358          | 0.3851    | 0.5794 | 0.4627 | 0.8667   |
| No log        | 7.0   | 91   | 0.5484          | 0.3491    | 0.5514 | 0.4275 | 0.8645   |
| No log        | 8.0   | 104  | 0.5671          | 0.3580    | 0.5421 | 0.4312 | 0.8672   |
| No log        | 9.0   | 117  | 0.5666          | 0.3494    | 0.5421 | 0.4249 | 0.8688   |
| No log        | 10.0  | 130  | 0.5677          | 0.3452    | 0.5421 | 0.4218 | 0.8688   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wikiann"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "wikiann", "type": "wikiann", "config": "ace", "split": "validation", "args": "ace"}, "metrics": [{"type": "precision", "value": 0.34523809523809523, "name": "Precision"}, {"type": "recall", "value": 0.5420560747663551, "name": "Recall"}, {"type": "f1", "value": 0.4218181818181818, "name": "F1"}, {"type": "accuracy", "value": 0.8688172043010752, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer dataset:wikiann license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-wikiann #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bert-finetuned-ner
==================


This model is a fine-tuned version of bert-base-cased on the wikiann dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5677
* Precision: 0.3452
* Recall: 0.5421
* F1: 0.4218
* Accuracy: 0.8688


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 4.29.2
* Pytorch 2.0.1+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: 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 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-wikiann #license-apache-2.0 #model-index #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 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3