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# ner_nerd

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the nerd dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2245
- Precision: 0.7466
- Recall: 0.7873
- F1: 0.7664
- Accuracy: 0.9392

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2843        | 1.0   | 8235  | 0.1951          | 0.7352    | 0.7824 | 0.7580 | 0.9375   |
| 0.1655        | 2.0   | 16470 | 0.1928          | 0.7519    | 0.7827 | 0.7670 | 0.9398   |
| 0.1216        | 3.0   | 24705 | 0.2119          | 0.75      | 0.7876 | 0.7684 | 0.9396   |
| 0.0881        | 4.0   | 32940 | 0.2258          | 0.7515    | 0.7896 | 0.7701 | 0.9392   |
| 0.0652        | 5.0   | 41175 | 0.2564          | 0.7518    | 0.7875 | 0.7692 | 0.9387   |


### Framework versions

- Transformers 4.9.1
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["nerd"], "metrics": ["precision", "recall", "f1", "accuracy"], "model_index": [{"name": "ner_nerd", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "dataset": {"name": "nerd", "type": "nerd", "args": "nerd"}, "metric": {"name": "Accuracy", "type": "accuracy", "value": 0.9391592461061087}}]}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer dataset:nerd license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-nerd #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

ner\_nerd
=========


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


* Loss: 0.2245
* Precision: 0.7466
* Recall: 0.7873
* F1: 0.7664
* Accuracy: 0.9392


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: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.9.1
* Pytorch 1.9.0+cu102
* Datasets 1.11.0
* Tokenizers 0.10.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.9.1
* Pytorch 1.9.0+cu102
* Datasets 1.11.0
* Tokenizers 0.10.2
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-nerd #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.9.1
* Pytorch 1.9.0+cu102
* Datasets 1.11.0
* Tokenizers 0.10.2
passage: TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-nerd #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 5### Training results### Framework versions


* Transformers 4.9.1
* Pytorch 1.9.0+cu102
* Datasets 1.11.0
* Tokenizers 0.10.2