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# Prototypeu/bart-base-finetuned-tldrhq-cnn-dailymail

This model is a fine-tuned version of [Prototypeu/bart-base-finetuned-xsum](https://huggingface.co/Prototypeu/bart-base-finetuned-xsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.5049
- Train Logits Loss: 1.5049
- Train Rouge1: 28.1795
- Train Rouge2: 14.0392
- Train Rougel: 23.7617
- Train Rougelsum: 26.5583
- Train Gen Len: 19.0
- 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 3e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 255113, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 32000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.98, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Train Logits Loss | Train Rouge1 | Train Rouge2 | Train Rougel | Train Rougelsum | Train Gen Len | Epoch |
|:----------:|:-----------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:|
| 2.9074     | 2.9074            | 26.9164      | 12.6984      | 22.4321      | 25.2287         | 19.0          | 0     |
| 1.9368     | 1.9368            | 28.0165      | 13.8906      | 23.4187      | 26.3779         | 19.0          | 1     |
| 1.7246     | 1.7246            | 27.6022      | 13.5255      | 23.2301      | 25.9923         | 19.0          | 2     |
| 1.5945     | 1.5945            | 28.0347      | 13.7045      | 23.4851      | 26.3488         | 19.0          | 3     |
| 1.5049     | 1.5049            | 28.1795      | 14.0392      | 23.7617      | 26.5583         | 19.0          | 4     |


### Framework versions

- Transformers 4.17.0
- TensorFlow 2.6.0
- Datasets 2.0.0
- Tokenizers 0.11.6

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "Prototypeu/bart-base-finetuned-tldrhq-cnn-dailymail", "results": []}]}
transformers tf tensorboard bart text2text-generation generated_from_keras_callback autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #tensorboard #bart #text2text-generation #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 

Prototypeu/bart-base-finetuned-tldrhq-cnn-dailymail
===================================================


This model is a fine-tuned version of Prototypeu/bart-base-finetuned-xsum on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 1.5049
* Train Logits Loss: 1.5049
* Train Rouge1: 28.1795
* Train Rouge2: 14.0392
* Train Rougel: 23.7617
* Train Rougelsum: 26.5583
* Train Gen Len: 19.0
* 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': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 3e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 3e-05, 'decay\_steps': 255113, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 32000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.98, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.17.0
* TensorFlow 2.6.0
* Datasets 2.0.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 3e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 3e-05, 'decay\_steps': 255113, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 32000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.98, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.17.0
* TensorFlow 2.6.0
* Datasets 2.0.0
* Tokenizers 0.11.6
TAGS
#transformers #tf #tensorboard #bart #text2text-generation #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 3e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 3e-05, 'decay\_steps': 255113, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 32000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.98, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.17.0
* TensorFlow 2.6.0
* Datasets 2.0.0
* Tokenizers 0.11.6
passage: TAGS
#transformers #tf #tensorboard #bart #text2text-generation #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 3e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 3e-05, 'decay\_steps': 255113, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 32000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.98, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.17.0
* TensorFlow 2.6.0
* Datasets 2.0.0
* Tokenizers 0.11.6