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# gpt2-synth-real

This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4267

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 21
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 80.0811       | 0.01  | 10   | 76.0005         |
| 63.2867       | 0.02  | 20   | 55.5177         |
| 30.7747       | 0.03  | 30   | 19.9807         |
| 17.8136       | 0.04  | 40   | 12.4432         |
| 6.5809        | 0.05  | 50   | 5.7868          |
| 3.8801        | 0.06  | 60   | 3.3238          |
| 2.2807        | 0.07  | 70   | 1.8328          |
| 1.3763        | 0.08  | 80   | 1.1114          |
| 0.8658        | 0.09  | 90   | 1.0464          |
| 0.748         | 0.1   | 100  | 0.8199          |
| 0.5694        | 0.12  | 110  | 0.5984          |
| 0.6427        | 0.13  | 120  | 0.6168          |
| 0.5534        | 0.14  | 130  | 0.5981          |
| 0.5483        | 0.15  | 140  | 0.5450          |
| 0.5384        | 0.16  | 150  | 0.4926          |
| 0.4926        | 0.17  | 160  | 0.4924          |
| 0.5059        | 0.18  | 170  | 0.4762          |
| 0.4372        | 0.19  | 180  | 0.4733          |
| 0.4833        | 0.2   | 190  | 0.4785          |
| 0.4511        | 0.21  | 200  | 0.4511          |
| 0.4163        | 0.22  | 210  | 0.4534          |
| 0.4849        | 0.23  | 220  | 0.4420          |
| 0.4857        | 0.24  | 230  | 0.4421          |
| 0.6163        | 0.25  | 240  | 0.4336          |
| 0.5151        | 0.26  | 250  | 0.4344          |
| 0.4533        | 0.27  | 260  | 0.4280          |
| 0.3812        | 0.28  | 270  | 0.4387          |
| 0.475         | 0.29  | 280  | 0.4274          |
| 0.4354        | 0.3   | 290  | 0.4272          |
| 0.3912        | 0.31  | 300  | 0.4305          |
| 0.3944        | 0.32  | 310  | 0.4204          |
| 0.4166        | 0.33  | 320  | 0.4239          |
| 0.3677        | 0.35  | 330  | 0.4246          |
| 0.4135        | 0.36  | 340  | 0.4267          |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.11.0+cu113
- Datasets 2.6.1
- Tokenizers 0.12.1

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

gpt2-synth-real
===============


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


* Loss: 0.4267


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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 4
* seed: 21
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3.0


### Training results



### Framework versions


* Transformers 4.24.0
* Pytorch 1.11.0+cu113
* Datasets 2.6.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 4
* seed: 21
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.11.0+cu113
* Datasets 2.6.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 4
* seed: 21
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.11.0+cu113
* Datasets 2.6.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 4
* seed: 21
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3.0### Training results### Framework versions


* Transformers 4.24.0
* Pytorch 1.11.0+cu113
* Datasets 2.6.1
* Tokenizers 0.12.1