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# distilgpt_oscarth_0060

This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 2.8883
- Validation Loss: 2.7784
- Epoch: 59

## 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': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 5.6021     | 4.5759          | 0     |
| 4.4536     | 4.1235          | 1     |
| 4.1386     | 3.9013          | 2     |
| 3.9546     | 3.7563          | 3     |
| 3.8255     | 3.6477          | 4     |
| 3.7271     | 3.5617          | 5     |
| 3.6488     | 3.4936          | 6     |
| 3.5844     | 3.4379          | 7     |
| 3.5301     | 3.3891          | 8     |
| 3.4833     | 3.3448          | 9     |
| 3.4427     | 3.3098          | 10    |
| 3.4068     | 3.2750          | 11    |
| 3.3749     | 3.2425          | 12    |
| 3.3462     | 3.2211          | 13    |
| 3.3202     | 3.1941          | 14    |
| 3.2964     | 3.1720          | 15    |
| 3.2749     | 3.1512          | 16    |
| 3.2548     | 3.1322          | 17    |
| 3.2363     | 3.1141          | 18    |
| 3.2188     | 3.0982          | 19    |
| 3.2025     | 3.0818          | 20    |
| 3.1871     | 3.0678          | 21    |
| 3.1724     | 3.0533          | 22    |
| 3.1583     | 3.0376          | 23    |
| 3.1446     | 3.0256          | 24    |
| 3.1318     | 3.0122          | 25    |
| 3.1195     | 3.0016          | 26    |
| 3.1079     | 2.9901          | 27    |
| 3.0968     | 2.9826          | 28    |
| 3.0863     | 2.9711          | 29    |
| 3.0761     | 2.9593          | 30    |
| 3.0665     | 2.9514          | 31    |
| 3.0572     | 2.9432          | 32    |
| 3.0483     | 2.9347          | 33    |
| 3.0396     | 2.9250          | 34    |
| 3.0313     | 2.9160          | 35    |
| 3.0232     | 2.9095          | 36    |
| 3.0153     | 2.9028          | 37    |
| 3.0078     | 2.8949          | 38    |
| 3.0004     | 2.8864          | 39    |
| 2.9932     | 2.8799          | 40    |
| 2.9864     | 2.8722          | 41    |
| 2.9797     | 2.8657          | 42    |
| 2.9731     | 2.8605          | 43    |
| 2.9668     | 2.8544          | 44    |
| 2.9606     | 2.8481          | 45    |
| 2.9545     | 2.8421          | 46    |
| 2.9487     | 2.8368          | 47    |
| 2.9429     | 2.8288          | 48    |
| 2.9374     | 2.8257          | 49    |
| 2.9319     | 2.8204          | 50    |
| 2.9266     | 2.8152          | 51    |
| 2.9215     | 2.8093          | 52    |
| 2.9164     | 2.8054          | 53    |
| 2.9114     | 2.7998          | 54    |
| 2.9066     | 2.7980          | 55    |
| 2.9019     | 2.7913          | 56    |
| 2.8972     | 2.7865          | 57    |
| 2.8927     | 2.7816          | 58    |
| 2.8883     | 2.7784          | 59    |


### Framework versions

- Transformers 4.20.1
- TensorFlow 2.8.2
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "distilgpt_oscarth_0060", "results": []}]}
transformers tf gpt2 text-generation generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #tf #gpt2 #text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

distilgpt\_oscarth\_0060
========================


This model is a fine-tuned version of distilgpt2 on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 2.8883
* Validation Loss: 2.7784
* Epoch: 59


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': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.20.1
* TensorFlow 2.8.2
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.20.1
* TensorFlow 2.8.2
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #tf #gpt2 #text-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': 'AdamWeightDecay', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.20.1
* TensorFlow 2.8.2
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #tf #gpt2 #text-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': 'AdamWeightDecay', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.20.1
* TensorFlow 2.8.2
* Datasets 2.3.2
* Tokenizers 0.12.1