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# CIS6930_DAAGR_T5_Emo

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3253
- Train Accuracy: 0.9647
- Validation Loss: 0.4468
- Validation Accuracy: 0.9495
- 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 0.001, '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 |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.4976     | 0.9412         | 0.4567          | 0.9459              | 0     |
| 0.4359     | 0.9482         | 0.4462          | 0.9474              | 1     |
| 0.4228     | 0.9502         | 0.4406          | 0.9484              | 2     |
| 0.4131     | 0.9517         | 0.4370          | 0.9488              | 3     |
| 0.4050     | 0.9528         | 0.4349          | 0.9493              | 4     |
| 0.3981     | 0.9539         | 0.4335          | 0.9496              | 5     |
| 0.3914     | 0.9548         | 0.4327          | 0.9498              | 6     |
| 0.3851     | 0.9558         | 0.4328          | 0.9500              | 7     |
| 0.3794     | 0.9565         | 0.4328          | 0.9501              | 8     |
| 0.3738     | 0.9574         | 0.4321          | 0.9502              | 9     |
| 0.3685     | 0.9582         | 0.4328          | 0.9502              | 10    |
| 0.3632     | 0.9589         | 0.4340          | 0.9502              | 11    |
| 0.3582     | 0.9597         | 0.4343          | 0.9501              | 12    |
| 0.3531     | 0.9605         | 0.4363          | 0.9501              | 13    |
| 0.3482     | 0.9612         | 0.4381          | 0.9501              | 14    |
| 0.3436     | 0.9619         | 0.4390          | 0.9500              | 15    |
| 0.3391     | 0.9626         | 0.4396          | 0.9500              | 16    |
| 0.3340     | 0.9633         | 0.4438          | 0.9499              | 17    |
| 0.3297     | 0.9640         | 0.4454          | 0.9498              | 18    |
| 0.3253     | 0.9647         | 0.4468          | 0.9495              | 19    |


### Framework versions

- Transformers 4.27.4
- TensorFlow 2.11.0
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "CIS6930_DAAGR_T5_Emo", "results": []}]}
transformers tf t5 text2text-generation generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #tf #t5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 

CIS6930\_DAAGR\_T5\_Emo
=======================


This model is a fine-tuned version of t5-small on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 0.3253
* Train Accuracy: 0.9647
* Validation Loss: 0.4468
* Validation Accuracy: 0.9495
* 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': 'Adam', 'weight\_decay': None, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': True, 'is\_legacy\_optimizer': False, 'learning\_rate': 0.001, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.27.4
* TensorFlow 2.11.0
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'weight\_decay': None, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': True, 'is\_legacy\_optimizer': False, 'learning\_rate': 0.001, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.27.4
* TensorFlow 2.11.0
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #tf #t5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'weight\_decay': None, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': True, 'is\_legacy\_optimizer': False, 'learning\_rate': 0.001, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.27.4
* TensorFlow 2.11.0
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #tf #t5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'weight\_decay': None, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': True, 'is\_legacy\_optimizer': False, 'learning\_rate': 0.001, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.27.4
* TensorFlow 2.11.0
* Datasets 2.11.0
* Tokenizers 0.13.2