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# Horovod_Tweet_Sentiment_1k_5eps

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: 0.5216092
- Train Accuracy: 0.784375
- Validation Loss: 0.92405033
- Validation Accuracy: 0.4875
- Epoch: 4

## 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': 'Adam', 'clipnorm': 1.0, 'learning_rate': 0.0003, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.7129049  | 0.50937504     | 0.7314203       | 0.490625            | 0     |
| 0.73165804 | 0.47343752     | 0.6929074       | 0.484375            | 1     |
| 0.6827939  | 0.55           | 0.6864271       | 0.50625             | 2     |
| 0.66076773 | 0.5578125      | 0.60817575      | 0.69687504          | 3     |
| 0.5216092  | 0.784375       | 0.92405033      | 0.4875              | 4     |


### Framework versions

- Transformers 4.17.0
- TensorFlow 2.6.0
- Tokenizers 0.11.6

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "Horovod_Tweet_Sentiment_1k_5eps", "results": []}]}
transformers tf bert text-classification generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

Horovod\_Tweet\_Sentiment\_1k\_5eps
===================================


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: 0.5216092
* Train Accuracy: 0.784375
* Validation Loss: 0.92405033
* Validation Accuracy: 0.4875
* Epoch: 4


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': 'Adam', 'clipnorm': 1.0, 'learning\_rate': 0.0003, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.17.0
* TensorFlow 2.6.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'clipnorm': 1.0, 'learning\_rate': 0.0003, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.17.0
* TensorFlow 2.6.0
* Tokenizers 0.11.6
TAGS
#transformers #tf #bert #text-classification #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': 'Adam', 'clipnorm': 1.0, 'learning\_rate': 0.0003, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.17.0
* TensorFlow 2.6.0
* Tokenizers 0.11.6
TAGS
#transformers #tf #bert #text-classification #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': 'Adam', 'clipnorm': 1.0, 'learning\_rate': 0.0003, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.17.0
* TensorFlow 2.6.0
* Tokenizers 0.11.6