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# bert-tiny-finetuned-ner

This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1689
- Precision: 0.8083
- Recall: 0.8274
- F1: 0.8177
- Accuracy: 0.9598

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0355        | 1.0   | 878  | 0.1692          | 0.8072    | 0.8248 | 0.8159 | 0.9594   |
| 0.0411        | 2.0   | 1756 | 0.1678          | 0.8101    | 0.8277 | 0.8188 | 0.9600   |
| 0.0386        | 3.0   | 2634 | 0.1697          | 0.8103    | 0.8269 | 0.8186 | 0.9599   |
| 0.0373        | 4.0   | 3512 | 0.1694          | 0.8106    | 0.8263 | 0.8183 | 0.9600   |
| 0.0383        | 5.0   | 4390 | 0.1689          | 0.8083    | 0.8274 | 0.8177 | 0.9598   |


### Framework versions

- Transformers 4.10.0
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "datasets": ["conll2003"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-tiny-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "conll2003", "type": "conll2003", "args": "conll2003"}, "metrics": [{"type": "precision", "value": 0.8083060109289617, "name": "Precision"}, {"type": "recall", "value": 0.8273856136033113, "name": "Recall"}, {"type": "f1", "value": 0.8177345348001547, "name": "F1"}, {"type": "accuracy", "value": 0.9597597979252387, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer dataset:conll2003 model-index autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-conll2003 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 

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


This model is a fine-tuned version of prajjwal1/bert-tiny on the conll2003 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1689
* Precision: 0.8083
* Recall: 0.8274
* F1: 0.8177
* Accuracy: 0.9598


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


### Training results



### Framework versions


* Transformers 4.10.0
* Pytorch 1.9.0+cu102
* Datasets 1.11.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.10.0
* Pytorch 1.9.0+cu102
* Datasets 1.11.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-conll2003 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.10.0
* Pytorch 1.9.0+cu102
* Datasets 1.11.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-conll2003 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5### Training results### Framework versions


* Transformers 4.10.0
* Pytorch 1.9.0+cu102
* Datasets 1.11.0
* Tokenizers 0.10.3