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# gpt2-kl_1_06-hs_cn

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: 0.5352

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 74.175        | 0.02  | 10   | 69.5742         |
| 46.6833       | 0.04  | 20   | 32.9573         |
| 14.147        | 0.06  | 30   | 10.6344         |
| 7.4081        | 0.08  | 40   | 4.2202          |
| 4.1981        | 0.1   | 50   | 2.0325          |
| 1.9903        | 0.12  | 60   | 1.0829          |
| 1.5743        | 0.14  | 70   | 0.8595          |
| 1.4537        | 0.16  | 80   | 0.7859          |
| 1.4022        | 0.18  | 90   | 0.7212          |
| 1.3332        | 0.2   | 100  | 0.6727          |
| 1.1681        | 0.22  | 110  | 0.6850          |
| 1.1991        | 0.24  | 120  | 0.5978          |
| 1.2297        | 0.26  | 130  | 0.6137          |
| 1.3475        | 0.28  | 140  | 0.5888          |
| 1.3468        | 0.3   | 150  | 0.5783          |
| 1.2516        | 0.32  | 160  | 0.5765          |
| 1.1055        | 0.34  | 170  | 0.5752          |
| 1.2874        | 0.36  | 180  | 0.5684          |
| 1.3511        | 0.38  | 190  | 0.5613          |
| 1.1492        | 0.4   | 200  | 0.5571          |
| 1.3802        | 0.42  | 210  | 0.5567          |
| 1.3072        | 0.44  | 220  | 0.5527          |
| 1.1026        | 0.46  | 230  | 0.5538          |
| 1.199         | 0.48  | 240  | 0.5497          |
| 1.1124        | 0.5   | 250  | 0.5513          |
| 1.1861        | 0.52  | 260  | 0.5495          |
| 1.1603        | 0.54  | 270  | 0.5434          |
| 1.2407        | 0.56  | 280  | 0.5451          |
| 1.1338        | 0.58  | 290  | 0.5437          |
| 1.0556        | 0.6   | 300  | 0.5428          |
| 1.2218        | 0.62  | 310  | 0.5392          |
| 1.3505        | 0.64  | 320  | 0.5408          |
| 1.1001        | 0.66  | 330  | 0.5426          |
| 1.1123        | 0.68  | 340  | 0.5385          |
| 1.1046        | 0.7   | 350  | 0.5385          |
| 1.1291        | 0.72  | 360  | 0.5383          |
| 1.2087        | 0.74  | 370  | 0.5378          |
| 1.1888        | 0.76  | 380  | 0.5380          |
| 1.1634        | 0.78  | 390  | 0.5363          |
| 1.249         | 0.8   | 400  | 0.5351          |
| 1.1197        | 0.82  | 410  | 0.5350          |
| 1.1508        | 0.84  | 420  | 0.5366          |
| 1.2025        | 0.86  | 430  | 0.5340          |
| 1.13          | 0.88  | 440  | 0.5347          |
| 1.1664        | 0.9   | 450  | 0.5371          |
| 1.048         | 0.92  | 460  | 0.5352          |


### 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_06-hs_cn", "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\_06-hs\_cn
=====================


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


* Loss: 0.5352


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