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# hsohn3/cchs-bert-visit-uncased-wordlevel-block512-batch4-ep60

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: 0.8314
- Epoch: 59

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Epoch |
|:----------:|:-----:|
| 3.8539     | 0     |
| 3.0645     | 1     |
| 3.0225     | 2     |
| 3.0128     | 3     |
| 3.0023     | 4     |
| 2.9834     | 5     |
| 2.9859     | 6     |
| 2.9814     | 7     |
| 2.9729     | 8     |
| 2.9736     | 9     |
| 2.9687     | 10    |
| 2.9665     | 11    |
| 2.9673     | 12    |
| 2.9612     | 13    |
| 2.9056     | 14    |
| 2.8781     | 15    |
| 2.8612     | 16    |
| 2.8259     | 17    |
| 2.8089     | 18    |
| 2.7865     | 19    |
| 2.7697     | 20    |
| 2.7307     | 21    |
| 2.6828     | 22    |
| 2.6168     | 23    |
| 2.5259     | 24    |
| 2.3860     | 25    |
| 2.2088     | 26    |
| 2.0192     | 27    |
| 1.8022     | 28    |
| 1.5856     | 29    |
| 1.4330     | 30    |
| 1.3441     | 31    |
| 1.2728     | 32    |
| 1.2154     | 33    |
| 1.1757     | 34    |
| 1.1411     | 35    |
| 1.1037     | 36    |
| 1.0883     | 37    |
| 1.0633     | 38    |
| 1.0368     | 39    |
| 1.0205     | 40    |
| 1.0047     | 41    |
| 0.9884     | 42    |
| 0.9754     | 43    |
| 0.9566     | 44    |
| 0.9427     | 45    |
| 0.9385     | 46    |
| 0.9246     | 47    |
| 0.9114     | 48    |
| 0.9029     | 49    |
| 0.8993     | 50    |
| 0.8850     | 51    |
| 0.8768     | 52    |
| 0.8701     | 53    |
| 0.8626     | 54    |
| 0.8580     | 55    |
| 0.8489     | 56    |
| 0.8407     | 57    |
| 0.8338     | 58    |
| 0.8314     | 59    |


### 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/cchs-bert-visit-uncased-wordlevel-block512-batch4-ep60", "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/cchs-bert-visit-uncased-wordlevel-block512-batch4-ep60
=============================================================


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: 0.8314
* Epoch: 59


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:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32


### 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': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### 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': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### 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': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32### Training results### Framework versions


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