
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# gpt-work-filter-auto-complete

This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0939

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 22   | 0.6395          |
| No log        | 2.0   | 44   | 0.6235          |
| No log        | 3.0   | 66   | 0.6035          |
| No log        | 4.0   | 88   | 0.5845          |
| No log        | 5.0   | 110  | 0.5645          |
| No log        | 6.0   | 132  | 0.5442          |
| No log        | 7.0   | 154  | 0.5346          |
| No log        | 8.0   | 176  | 0.5167          |
| No log        | 9.0   | 198  | 0.5009          |
| No log        | 10.0  | 220  | 0.4893          |
| No log        | 11.0  | 242  | 0.4676          |
| No log        | 12.0  | 264  | 0.4498          |
| No log        | 13.0  | 286  | 0.4382          |
| No log        | 14.0  | 308  | 0.4276          |
| No log        | 15.0  | 330  | 0.4132          |
| No log        | 16.0  | 352  | 0.4075          |
| No log        | 17.0  | 374  | 0.3952          |
| No log        | 18.0  | 396  | 0.3822          |
| No log        | 19.0  | 418  | 0.3677          |
| No log        | 20.0  | 440  | 0.3563          |
| No log        | 21.0  | 462  | 0.3495          |
| No log        | 22.0  | 484  | 0.3455          |
| 0.6366        | 23.0  | 506  | 0.3316          |
| 0.6366        | 24.0  | 528  | 0.3126          |
| 0.6366        | 25.0  | 550  | 0.3118          |
| 0.6366        | 26.0  | 572  | 0.3021          |
| 0.6366        | 27.0  | 594  | 0.2944          |
| 0.6366        | 28.0  | 616  | 0.2878          |
| 0.6366        | 29.0  | 638  | 0.2772          |
| 0.6366        | 30.0  | 660  | 0.2701          |
| 0.6366        | 31.0  | 682  | 0.2643          |
| 0.6366        | 32.0  | 704  | 0.2576          |
| 0.6366        | 33.0  | 726  | 0.2514          |
| 0.6366        | 34.0  | 748  | 0.2467          |
| 0.6366        | 35.0  | 770  | 0.2359          |
| 0.6366        | 36.0  | 792  | 0.2326          |
| 0.6366        | 37.0  | 814  | 0.2205          |
| 0.6366        | 38.0  | 836  | 0.2182          |
| 0.6366        | 39.0  | 858  | 0.2137          |
| 0.6366        | 40.0  | 880  | 0.2086          |
| 0.6366        | 41.0  | 902  | 0.2058          |
| 0.6366        | 42.0  | 924  | 0.1979          |
| 0.6366        | 43.0  | 946  | 0.1930          |
| 0.6366        | 44.0  | 968  | 0.1922          |
| 0.6366        | 45.0  | 990  | 0.1853          |
| 0.4122        | 46.0  | 1012 | 0.1800          |
| 0.4122        | 47.0  | 1034 | 0.1787          |
| 0.4122        | 48.0  | 1056 | 0.1738          |
| 0.4122        | 49.0  | 1078 | 0.1689          |
| 0.4122        | 50.0  | 1100 | 0.1670          |
| 0.4122        | 51.0  | 1122 | 0.1583          |
| 0.4122        | 52.0  | 1144 | 0.1560          |
| 0.4122        | 53.0  | 1166 | 0.1540          |
| 0.4122        | 54.0  | 1188 | 0.1507          |
| 0.4122        | 55.0  | 1210 | 0.1475          |
| 0.4122        | 56.0  | 1232 | 0.1452          |
| 0.4122        | 57.0  | 1254 | 0.1458          |
| 0.4122        | 58.0  | 1276 | 0.1425          |
| 0.4122        | 59.0  | 1298 | 0.1377          |
| 0.4122        | 60.0  | 1320 | 0.1338          |
| 0.4122        | 61.0  | 1342 | 0.1365          |
| 0.4122        | 62.0  | 1364 | 0.1278          |
| 0.4122        | 63.0  | 1386 | 0.1272          |
| 0.4122        | 64.0  | 1408 | 0.1253          |
| 0.4122        | 65.0  | 1430 | 0.1251          |
| 0.4122        | 66.0  | 1452 | 0.1217          |
| 0.4122        | 67.0  | 1474 | 0.1219          |
| 0.4122        | 68.0  | 1496 | 0.1177          |
| 0.3005        | 69.0  | 1518 | 0.1174          |
| 0.3005        | 70.0  | 1540 | 0.1155          |
| 0.3005        | 71.0  | 1562 | 0.1144          |
| 0.3005        | 72.0  | 1584 | 0.1127          |
| 0.3005        | 73.0  | 1606 | 0.1106          |
| 0.3005        | 74.0  | 1628 | 0.1098          |
| 0.3005        | 75.0  | 1650 | 0.1092          |
| 0.3005        | 76.0  | 1672 | 0.1067          |
| 0.3005        | 77.0  | 1694 | 0.1086          |
| 0.3005        | 78.0  | 1716 | 0.1042          |
| 0.3005        | 79.0  | 1738 | 0.1051          |
| 0.3005        | 80.0  | 1760 | 0.1038          |
| 0.3005        | 81.0  | 1782 | 0.1022          |
| 0.3005        | 82.0  | 1804 | 0.1015          |
| 0.3005        | 83.0  | 1826 | 0.1004          |
| 0.3005        | 84.0  | 1848 | 0.1003          |
| 0.3005        | 85.0  | 1870 | 0.0978          |
| 0.3005        | 86.0  | 1892 | 0.0987          |
| 0.3005        | 87.0  | 1914 | 0.0974          |
| 0.3005        | 88.0  | 1936 | 0.0975          |
| 0.3005        | 89.0  | 1958 | 0.0965          |
| 0.3005        | 90.0  | 1980 | 0.0960          |
| 0.2455        | 91.0  | 2002 | 0.0958          |
| 0.2455        | 92.0  | 2024 | 0.0952          |
| 0.2455        | 93.0  | 2046 | 0.0952          |
| 0.2455        | 94.0  | 2068 | 0.0944          |
| 0.2455        | 95.0  | 2090 | 0.0943          |
| 0.2455        | 96.0  | 2112 | 0.0940          |
| 0.2455        | 97.0  | 2134 | 0.0942          |
| 0.2455        | 98.0  | 2156 | 0.0940          |
| 0.2455        | 99.0  | 2178 | 0.0939          |
| 0.2455        | 100.0 | 2200 | 0.0939          |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt-work-filter-auto-complete", "results": []}]}
transformers pytorch tensorboard gpt2 text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

gpt-work-filter-auto-complete
=============================


This model is a fine-tuned version of distilgpt2 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0939


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: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3