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# cv_summarization-t5-small

This model is a fine-tuned version of [gopalkalpande/t5-small-finetuned-bbc-news-summarization](https://huggingface.co/gopalkalpande/t5-small-finetuned-bbc-news-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.8053
- Validation Loss: 0.7027
- Train Rougel: tf.Tensor(0.3339088, shape=(), dtype=float32)
- Epoch: 9

## 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': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Rougel                                   | Epoch |
|:----------:|:---------------:|:----------------------------------------------:|:-----:|
| 1.9068     | 1.5592          | tf.Tensor(0.31806523, shape=(), dtype=float32) | 0     |
| 1.6027     | 1.3316          | tf.Tensor(0.30698553, shape=(), dtype=float32) | 1     |
| 1.4177     | 1.1818          | tf.Tensor(0.30701882, shape=(), dtype=float32) | 2     |
| 1.2744     | 1.0718          | tf.Tensor(0.30627215, shape=(), dtype=float32) | 3     |
| 1.1618     | 0.9846          | tf.Tensor(0.3005299, shape=(), dtype=float32)  | 4     |
| 1.0575     | 0.9088          | tf.Tensor(0.2958022, shape=(), dtype=float32)  | 5     |
| 0.9764     | 0.8441          | tf.Tensor(0.30608675, shape=(), dtype=float32) | 6     |
| 0.9196     | 0.7895          | tf.Tensor(0.31722832, shape=(), dtype=float32) | 7     |
| 0.8478     | 0.7411          | tf.Tensor(0.3254477, shape=(), dtype=float32)  | 8     |
| 0.8053     | 0.7027          | tf.Tensor(0.3339088, shape=(), dtype=float32)  | 9     |


### Framework versions

- Transformers 4.30.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3

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

cv\_summarization-t5-small
==========================


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


* Train Loss: 0.8053
* Validation Loss: 0.7027
* Train Rougel: tf.Tensor(0.3339088, shape=(), dtype=float32)
* Epoch: 9


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': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.30.1
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.30.1
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #t5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.30.1
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3