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# gpt2-synth

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: 0.1783

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 73.0212       | 0.02  | 10   | 65.7853         |
| 38.3819       | 0.04  | 20   | 20.2835         |
| 11.6035       | 0.07  | 30   | 9.2104          |
| 7.5582        | 0.09  | 40   | 3.6178          |
| 2.1601        | 0.11  | 50   | 1.5943          |
| 0.9769        | 0.13  | 60   | 0.9299          |
| 0.7577        | 0.15  | 70   | 0.6257          |
| 0.5434        | 0.18  | 80   | 0.4690          |
| 0.4756        | 0.2   | 90   | 0.5805          |
| 0.4247        | 0.22  | 100  | 0.3353          |
| 0.3179        | 0.24  | 110  | 0.2710          |
| 0.2476        | 0.26  | 120  | 0.2642          |
| 0.2604        | 0.29  | 130  | 0.2667          |
| 0.212         | 0.31  | 140  | 0.2723          |
| 0.2819        | 0.33  | 150  | 0.2356          |
| 0.2693        | 0.35  | 160  | 0.2283          |
| 0.2415        | 0.37  | 170  | 0.2297          |
| 0.2237        | 0.4   | 180  | 0.2207          |
| 0.2412        | 0.42  | 190  | 0.2204          |
| 0.2245        | 0.44  | 200  | 0.2191          |
| 0.2641        | 0.46  | 210  | 0.2112          |
| 0.22          | 0.48  | 220  | 0.2096          |
| 0.1912        | 0.51  | 230  | 0.2096          |
| 0.2152        | 0.53  | 240  | 0.2067          |
| 0.2497        | 0.55  | 250  | 0.2028          |
| 0.2042        | 0.57  | 260  | 0.2025          |
| 0.2263        | 0.59  | 270  | 0.2003          |
| 0.2047        | 0.62  | 280  | 0.1994          |
| 0.2081        | 0.64  | 290  | 0.1979          |
| 0.203         | 0.66  | 300  | 0.1954          |
| 0.1872        | 0.68  | 310  | 0.1954          |
| 0.1669        | 0.7   | 320  | 0.1958          |
| 0.1845        | 0.73  | 330  | 0.1935          |
| 0.1917        | 0.75  | 340  | 0.1913          |
| 0.2066        | 0.77  | 350  | 0.1880          |
| 0.1873        | 0.79  | 360  | 0.1880          |
| 0.1889        | 0.81  | 370  | 0.1867          |
| 0.2196        | 0.84  | 380  | 0.1853          |
| 0.2062        | 0.86  | 390  | 0.1848          |
| 0.1802        | 0.88  | 400  | 0.1836          |
| 0.1754        | 0.9   | 410  | 0.1828          |
| 0.1997        | 0.92  | 420  | 0.1813          |
| 0.2072        | 0.95  | 430  | 0.1790          |
| 0.19          | 0.97  | 440  | 0.1774          |
| 0.2208        | 0.99  | 450  | 0.1785          |
| 0.1706        | 1.01  | 460  | 0.1790          |
| 0.1534        | 1.03  | 470  | 0.1783          |


### 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", "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
==========


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


* Loss: 0.1783


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