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# gpt2-maptask-GF

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7116

## 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: 2e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.0139        | 0.84  | 1000  | 2.9045          |
| 2.7923        | 1.67  | 2000  | 2.7825          |
| 2.6799        | 2.51  | 3000  | 2.7264          |
| 2.607         | 3.34  | 4000  | 2.6917          |
| 2.55          | 4.18  | 5000  | 2.6708          |
| 2.4988        | 5.01  | 6000  | 2.6570          |
| 2.4697        | 5.85  | 7000  | 2.6480          |
| 2.426         | 6.68  | 8000  | 2.6452          |
| 2.4031        | 7.52  | 9000  | 2.6404          |
| 2.3654        | 8.35  | 10000 | 2.6416          |
| 2.3471        | 9.19  | 11000 | 2.6418          |
| 2.3195        | 10.03 | 12000 | 2.6444          |
| 2.2969        | 10.86 | 13000 | 2.6455          |
| 2.2767        | 11.7  | 14000 | 2.6489          |
| 2.2608        | 12.53 | 15000 | 2.6525          |
| 2.2381        | 13.37 | 16000 | 2.6563          |
| 2.2228        | 14.2  | 17000 | 2.6602          |
| 2.2037        | 15.04 | 18000 | 2.6641          |
| 2.1911        | 15.87 | 19000 | 2.6684          |
| 2.1742        | 16.71 | 20000 | 2.6739          |
| 2.1626        | 17.54 | 21000 | 2.6776          |
| 2.1504        | 18.38 | 22000 | 2.6800          |
| 2.143         | 19.21 | 23000 | 2.6832          |
| 2.1277        | 20.05 | 24000 | 2.6892          |
| 2.1178        | 20.89 | 25000 | 2.6924          |
| 2.1128        | 21.72 | 26000 | 2.6952          |
| 2.1009        | 22.56 | 27000 | 2.6978          |
| 2.0957        | 23.39 | 28000 | 2.7006          |
| 2.0885        | 24.23 | 29000 | 2.7024          |
| 2.0849        | 25.06 | 30000 | 2.7065          |
| 2.0794        | 25.9  | 31000 | 2.7075          |
| 2.0783        | 26.73 | 32000 | 2.7090          |
| 2.0698        | 27.57 | 33000 | 2.7106          |
| 2.0718        | 28.4  | 34000 | 2.7109          |
| 2.069         | 29.24 | 35000 | 2.7116          |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt2-maptask-GF", "results": []}]}
transformers pytorch tensorboard gpt2 text-generation generated_from_trainer license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

gpt2-maptask-GF
===============


This model is a fine-tuned version of gpt2 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.7116


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: 2e-06
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-06
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #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: 2e-06
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #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: 2e-06
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 30### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1