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# pminhyung12/gpt2-base-v0

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the corpus_v1 dataset.
It achieves the following results on the evaluation set:
- Train Loss: 5.1058
- Validation Loss: 6.2552
- Epoch: 7

## 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': 'AdamW', 'weight_decay': 0.004, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 1e-04, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: mixed_bfloat16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 0.9128     | 0.9515          | 0     |
| 0.6172     | 0.8965          | 1     |
| 0.5713     | 0.8763          | 2     |
| 1.2088     | 1.8300          | 3     |
| 3.6887     | 5.8700          | 4     |
| 2.8920     | 3.6422          | 5     |
| 3.8045     | 8.9555          | 6     |
| 5.1058     | 6.2552          | 7     |


### Framework versions

- Transformers 4.26.1
- TensorFlow 2.12.0
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_keras_callback"], "datasets": ["corpus_v1"], "model-index": [{"name": "pminhyung12/gpt2-base-v0", "results": []}]}
transformers tf gpt2 text-generation generated_from_keras_callback dataset:corpus_v1 license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #tf #gpt2 #text-generation #generated_from_keras_callback #dataset-corpus_v1 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

pminhyung12/gpt2-base-v0
========================


This model is a fine-tuned version of gpt2 on the corpus\_v1 dataset.
It achieves the following results on the evaluation set:


* Train Loss: 5.1058
* Validation Loss: 6.2552
* Epoch: 7


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': 'AdamW', 'weight\_decay': 0.004, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': False, 'is\_legacy\_optimizer': False, 'learning\_rate': 1e-04, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: mixed\_bfloat16


### Training results



### Framework versions


* Transformers 4.26.1
* TensorFlow 2.12.0
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamW', 'weight\_decay': 0.004, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': False, 'is\_legacy\_optimizer': False, 'learning\_rate': 1e-04, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: mixed\_bfloat16 ### Training results ### Framework versions


* Transformers 4.26.1
* TensorFlow 2.12.0
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #tf #gpt2 #text-generation #generated_from_keras_callback #dataset-corpus_v1 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamW', 'weight\_decay': 0.004, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': False, 'is\_legacy\_optimizer': False, 'learning\_rate': 1e-04, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: mixed\_bfloat16 ### Training results ### Framework versions


* Transformers 4.26.1
* TensorFlow 2.12.0
* Datasets 2.9.0
* Tokenizers 0.13.2