
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# gpt_image_clef1

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.1002
- Train Rouge: 0.4943
- Validation Loss: 0.9385
- Validation Rouge: 0.4581
- Epoch: 8

## 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': 0.0005, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0005, 'decay_steps': 2554800, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.99, 'epsilon': 0.2, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Train Rouge | Validation Loss | Validation Rouge | Epoch |
|:----------:|:-----------:|:---------------:|:----------------:|:-----:|
| 1.5411     | 0.4201      | 1.0250          | 0.4297           | 0     |
| 1.1803     | 0.4674      | 0.9795          | 0.4437           | 1     |
| 1.1391     | 0.4801      | 0.9588          | 0.4523           | 2     |
| 1.1168     | 0.4869      | 0.9395          | 0.4590           | 3     |
| 1.1038     | 0.4912      | 0.9318          | 0.4613           | 4     |
| 1.0971     | 0.4934      | 0.9305          | 0.4611           | 5     |
| 1.0949     | 0.4945      | 0.9287          | 0.4621           | 6     |
| 1.0965     | 0.4948      | 0.9313          | 0.4605           | 7     |
| 1.1002     | 0.4943      | 0.9385          | 0.4581           | 8     |


### Framework versions

- Transformers 4.28.1
- TensorFlow 2.10.1
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "gpt_image_clef1", "results": []}]}
transformers tf gpt2 text-generation generated_from_keras_callback license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #tf #gpt2 #text-generation #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

gpt\_image\_clef1
=================


This model is a fine-tuned version of gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 1.1002
* Train Rouge: 0.4943
* Validation Loss: 0.9385
* Validation Rouge: 0.4581
* Epoch: 8


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': 0.0005, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 0.0005, 'decay\_steps': 2554800, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.99, 'epsilon': 0.2, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.28.1
* TensorFlow 2.10.1
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 0.0005, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 0.0005, 'decay\_steps': 2554800, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.99, 'epsilon': 0.2, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.10.1
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #gpt2 #text-generation #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 0.0005, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 0.0005, 'decay\_steps': 2554800, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.99, 'epsilon': 0.2, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.10.1
* Datasets 2.11.0
* Tokenizers 0.13.3