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# tw-sentiment-finetuned

This model is a fine-tuned version of [distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert-base-cased-distilled-squad) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.2039
- Train Accuracy: 0.9171
- Validation Loss: 0.4805
- Validation Accuracy: 0.8237
- 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': 'AdamWeightDecay', 'learning_rate': 5e-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 | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.4620     | 0.7977         | 0.3893          | 0.8332              | 0     |
| 0.3238     | 0.8596         | 0.4674          | 0.8362              | 1     |
| 0.2039     | 0.9171         | 0.4805          | 0.8237              | 2     |


### Framework versions

- Transformers 4.26.0
- TensorFlow 2.9.2
- Tokenizers 0.13.2
{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "metrics": ["accuracy"], "model-index": [{"name": "tw-sentiment-finetuned", "results": []}]}
transformers tf distilbert text-classification generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #tf #distilbert #text-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 

tw-sentiment-finetuned
======================


This model is a fine-tuned version of distilbert-base-cased-distilled-squad on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 0.2039
* Train Accuracy: 0.9171
* Validation Loss: 0.4805
* Validation Accuracy: 0.8237
* 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': 'AdamWeightDecay', 'learning\_rate': 5e-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 4.26.0
* TensorFlow 2.9.2
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 5e-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 4.26.0
* TensorFlow 2.9.2
* Tokenizers 0.13.2
TAGS
#transformers #tf #distilbert #text-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 5e-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 4.26.0
* TensorFlow 2.9.2
* Tokenizers 0.13.2
TAGS
#transformers #tf #distilbert #text-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 5e-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 4.26.0
* TensorFlow 2.9.2
* Tokenizers 0.13.2