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# gpt2-kl_1_05-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: 0.5428

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 73.9843       | 0.02  | 10   | 69.5786         |
| 46.5197       | 0.04  | 20   | 32.9833         |
| 13.9523       | 0.06  | 30   | 10.6378         |
| 7.2147        | 0.08  | 40   | 4.2578          |
| 3.4244        | 0.1   | 50   | 2.0277          |
| 1.8713        | 0.12  | 60   | 1.0949          |
| 1.5036        | 0.14  | 70   | 0.9420          |
| 1.2167        | 0.16  | 80   | 0.7558          |
| 1.1629        | 0.18  | 90   | 0.6537          |
| 1.0997        | 0.2   | 100  | 0.6998          |
| 1.0395        | 0.22  | 110  | 0.5946          |
| 0.9896        | 0.24  | 120  | 0.5825          |
| 1.0067        | 0.26  | 130  | 0.5759          |
| 1.0529        | 0.28  | 140  | 0.5738          |
| 1.072         | 0.3   | 150  | 0.5701          |
| 0.9853        | 0.32  | 160  | 0.5668          |
| 0.8855        | 0.34  | 170  | 0.5685          |
| 1.0401        | 0.36  | 180  | 0.5600          |
| 1.0669        | 0.38  | 190  | 0.5558          |
| 0.9189        | 0.4   | 200  | 0.5505          |
| 1.1044        | 0.42  | 210  | 0.5526          |
| 1.0624        | 0.44  | 220  | 0.5470          |
| 0.8628        | 0.46  | 230  | 0.5493          |
| 0.9359        | 0.48  | 240  | 0.5452          |
| 0.8814        | 0.5   | 250  | 0.5466          |
| 0.9381        | 0.52  | 260  | 0.5447          |
| 0.8973        | 0.54  | 270  | 0.5418          |
| 0.9575        | 0.56  | 280  | 0.5438          |
| 0.8965        | 0.58  | 290  | 0.5434          |
| 0.837         | 0.6   | 300  | 0.5428          |


### 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_05-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\_05-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: 0.5428


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