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# xinyixiuxiu/albert-xlarge-v2-SST2-finetuned

This model is a fine-tuned version of [albert-xlarge-v2](https://huggingface.co/albert-xlarge-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0995
- Train Accuracy: 0.9666
- Validation Loss: 0.2012
- Validation Accuracy: 0.9381
- Epoch: 2

## 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', 'learning_rate': 3e-06, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.2577     | 0.8879         | 0.1899          | 0.9278              | 0     |
| 0.1339     | 0.9530         | 0.1549          | 0.9507              | 1     |
| 0.0995     | 0.9666         | 0.2012          | 0.9381              | 2     |


### Framework versions

- Transformers 4.21.1
- TensorFlow 2.7.0
- Datasets 2.10.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "xinyixiuxiu/albert-xlarge-v2-SST2-finetuned", "results": []}]}
transformers tf albert text-classification generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #albert #text-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

xinyixiuxiu/albert-xlarge-v2-SST2-finetuned
===========================================


This model is a fine-tuned version of albert-xlarge-v2 on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 0.0995
* Train Accuracy: 0.9666
* Validation Loss: 0.2012
* Validation Accuracy: 0.9381
* Epoch: 2


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', 'learning\_rate': 3e-06, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.21.1
* TensorFlow 2.7.0
* Datasets 2.10.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 3e-06, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.21.1
* TensorFlow 2.7.0
* Datasets 2.10.1
* Tokenizers 0.12.1
TAGS
#transformers #tf #albert #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', 'learning\_rate': 3e-06, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.21.1
* TensorFlow 2.7.0
* Datasets 2.10.1
* Tokenizers 0.12.1