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# mekjr1/Feel-bert-base-uncased-trial-vent

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: 3.0961
- Validation Loss: 3.2267
- Epoch: 19

## 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': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -992, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 3.1524     | 2.8831          | 0     |
| 3.3046     | 2.9650          | 1     |
| 3.3182     | 2.2945          | 2     |
| 3.2669     | 3.1812          | 3     |
| 3.1702     | 2.7750          | 4     |
| 3.2273     | 2.0445          | 5     |
| 3.2955     | 2.7407          | 6     |
| 3.1915     | 3.0679          | 7     |
| 3.2005     | 2.0120          | 8     |
| 3.0654     | 2.3347          | 9     |
| 3.0985     | 2.9339          | 10    |
| 3.0161     | 2.8847          | 11    |
| 3.1455     | 3.1531          | 12    |
| 3.1237     | 3.3190          | 13    |
| 3.1059     | 2.5587          | 14    |
| 3.0486     | 2.8180          | 15    |
| 2.9230     | 2.2432          | 16    |
| 3.0667     | 3.0650          | 17    |
| 2.9550     | 2.4731          | 18    |
| 3.0961     | 3.2267          | 19    |


### Framework versions

- Transformers 4.26.1
- TensorFlow 2.11.0
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "mekjr1/Feel-bert-base-uncased-trial-vent", "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 

mekjr1/Feel-bert-base-uncased-trial-vent
========================================


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: 3.0961
* Validation Loss: 3.2267
* Epoch: 19


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': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': -992, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: mixed\_float16


### Training results



### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': -992, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: mixed\_float16 ### Training results ### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.9.0
* Tokenizers 0.13.2
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': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': -992, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: mixed\_float16 ### Training results ### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.9.0
* Tokenizers 0.13.2