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# hsohn3/ehr-bert-base-uncased-cchs-wordlevel

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 3.7374
- Epoch: 9

## Model description

- model: bert-base-uncased (train from scratch)
- tokenizer: BertTokenizer + WordLevel splitter

## Intended uses & limitations

More information needed

## Training and evaluation data

- data_source: cchs (10,000 visits)
- data_format: visit-level texts concatenated by `[SEP]` token

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-04, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
- block_size: 512
- batch_size: 4
- num_epochs: 10
- mlm_probability: 0.15

### Training results

| Train Loss | Epoch |
|:----------:|:-----:|
| 3.8857     | 0     |
| 3.7525     | 1     |
| 3.7505     | 2     |
| 3.7493     | 3     |
| 3.7412     | 4     |
| 3.7432     | 5     |
| 3.7428     | 6     |
| 3.7409     | 7     |
| 3.7394     | 8     |
| 3.7374     | 9     |


### Framework versions

- Transformers 4.20.1
- TensorFlow 2.8.2
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "hsohn3/ehr-bert-base-uncased-cchs-wordlevel", "results": []}]}
transformers tf bert fill-mask generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #bert #fill-mask #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

hsohn3/ehr-bert-base-uncased-cchs-wordlevel
===========================================


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


* Train Loss: 3.7374
* Epoch: 9


Model description
-----------------


* model: bert-base-uncased (train from scratch)
* tokenizer: BertTokenizer + WordLevel splitter


Intended uses & limitations
---------------------------


More information needed


Training and evaluation data
----------------------------


* data\_source: cchs (10,000 visits)
* data\_format: visit-level texts concatenated by '[SEP]' token


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 1e-04, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32
* block\_size: 512
* batch\_size: 4
* num\_epochs: 10
* mlm\_probability: 0.15


### Training results



### Framework versions


* Transformers 4.20.1
* TensorFlow 2.8.2
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 1e-04, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32
* block\_size: 512
* batch\_size: 4
* num\_epochs: 10
* mlm\_probability: 0.15 ### Training results ### Framework versions


* Transformers 4.20.1
* TensorFlow 2.8.2
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #tf #bert #fill-mask #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 1e-04, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32
* block\_size: 512
* batch\_size: 4
* num\_epochs: 10
* mlm\_probability: 0.15 ### Training results ### Framework versions


* Transformers 4.20.1
* TensorFlow 2.8.2
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #tf #bert #fill-mask #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 1e-04, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32
* block\_size: 512
* batch\_size: 4
* num\_epochs: 10
* mlm\_probability: 0.15### Training results### Framework versions


* Transformers 4.20.1
* TensorFlow 2.8.2
* Datasets 2.3.2
* Tokenizers 0.12.1