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# distilgpt2_fine_tuned_gcode

This model is a fine-tuned version of [congcongwang/distilgpt2_fine_tuned_coder](https://huggingface.co/congcongwang/distilgpt2_fine_tuned_coder) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.1670

## 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:
- learning_rate: 0.1
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 4.1754        | 1.0   | 52144 | 4.1670          |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.1
- Datasets 2.1.0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "model-index": [{"name": "distilgpt2_fine_tuned_gcode", "results": []}]}
transformers pytorch tensorboard gpt2 text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

distilgpt2\_fine\_tuned\_gcode
==============================


This model is a fine-tuned version of congcongwang/distilgpt2\_fine\_tuned\_coder on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 4.1670


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:


* learning\_rate: 0.1
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1


### Training results



### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.1
* Datasets 2.1.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.1
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.1
* Datasets 2.1.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.1
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.1
* Datasets 2.1.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.1
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1### Training results### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.1
* Datasets 2.1.0
* Tokenizers 0.10.3