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# gpt2-kl_1_07-hs_cn_decay

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: 0.5387

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 74.3927       | 0.02  | 10   | 69.5741         |
| 46.8756       | 0.04  | 20   | 32.9634         |
| 14.3637       | 0.06  | 30   | 10.6462         |
| 7.5685        | 0.08  | 40   | 4.2441          |
| 4.4164        | 0.1   | 50   | 2.0652          |
| 2.2355        | 0.12  | 60   | 1.1276          |
| 1.7411        | 0.14  | 70   | 0.8881          |
| 1.5599        | 0.16  | 80   | 0.7747          |
| 1.5609        | 0.18  | 90   | 0.6453          |
| 1.4701        | 0.2   | 100  | 0.6145          |
| 1.3214        | 0.22  | 110  | 0.6367          |
| 1.3795        | 0.24  | 120  | 0.6098          |
| 1.3714        | 0.26  | 130  | 0.5903          |
| 1.5096        | 0.28  | 140  | 0.5764          |
| 1.4983        | 0.3   | 150  | 0.5695          |
| 1.3707        | 0.32  | 160  | 0.5712          |
| 1.2352        | 0.34  | 170  | 0.5689          |
| 1.4272        | 0.36  | 180  | 0.5650          |
| 1.4578        | 0.38  | 190  | 0.5599          |
| 1.2548        | 0.4   | 200  | 0.5577          |
| 1.488         | 0.42  | 210  | 0.5575          |
| 1.3988        | 0.44  | 220  | 0.5518          |
| 1.1963        | 0.46  | 230  | 0.5536          |
| 1.2992        | 0.48  | 240  | 0.5519          |
| 1.1852        | 0.5   | 250  | 0.5517          |
| 1.2691        | 0.52  | 260  | 0.5473          |
| 1.2183        | 0.54  | 270  | 0.5433          |
| 1.3085        | 0.56  | 280  | 0.5443          |
| 1.1756        | 0.58  | 290  | 0.5422          |
| 1.1152        | 0.6   | 300  | 0.5420          |
| 1.2707        | 0.62  | 310  | 0.5391          |
| 1.3634        | 0.64  | 320  | 0.5376          |
| 1.1368        | 0.66  | 330  | 0.5378          |
| 1.1393        | 0.68  | 340  | 0.5378          |
| 1.1335        | 0.7   | 350  | 0.5387          |


### Framework versions

- Transformers 4.28.0
- Pytorch 1.11.0+cu113
- Datasets 2.11.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt2-kl_1_07-hs_cn_decay", "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-kl\_1\_07-hs\_cn\_decay
============================


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


* Loss: 0.5387


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 4.28.0
* Pytorch 1.11.0+cu113
* Datasets 2.11.0
* 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 4.28.0
* Pytorch 1.11.0+cu113
* Datasets 2.11.0
* 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 4.28.0
* Pytorch 1.11.0+cu113
* Datasets 2.11.0
* 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 4.28.0
* Pytorch 1.11.0+cu113
* Datasets 2.11.0
* Tokenizers 0.12.1