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# finetuned-test-1

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8192

## 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.8219        | 1.0   | 30   | 2.3343          |
| 2.4148        | 2.0   | 60   | 2.2010          |
| 2.3236        | 3.0   | 90   | 2.1442          |
| 2.2231        | 4.0   | 120  | 2.1651          |
| 2.2171        | 5.0   | 150  | 2.0614          |
| 2.127         | 6.0   | 180  | 2.0405          |
| 2.0748        | 7.0   | 210  | 2.0092          |
| 2.0511        | 8.0   | 240  | 1.9798          |
| 2.0097        | 9.0   | 270  | 1.8662          |
| 1.9969        | 10.0  | 300  | 1.9257          |
| 2.0006        | 11.0  | 330  | 1.9386          |
| 1.9273        | 12.0  | 360  | 1.9357          |
| 1.9177        | 13.0  | 390  | 1.8983          |
| 1.9128        | 14.0  | 420  | 1.8990          |
| 1.8979        | 15.0  | 450  | 1.9037          |
| 1.8721        | 16.0  | 480  | 1.8440          |
| 1.8998        | 17.0  | 510  | 1.8404          |
| 1.8862        | 18.0  | 540  | 1.9193          |
| 1.9133        | 19.0  | 570  | 1.8494          |
| 1.8799        | 20.0  | 600  | 1.8192          |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["conll2003"], "model-index": [{"name": "finetuned-test-1", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer dataset:conll2003 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

finetuned-test-1
================


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


* Loss: 1.8192


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: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1



### 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: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #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: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #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: 20
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1