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# gpt2-large-NaturalQuestions_2000-ep20

This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5184

## 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-05
- train_batch_size: 12
- eval_batch_size: 24
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2377        | 0.3   | 50   | 1.0267          |
| 1.0948        | 0.6   | 100  | 0.9831          |
| 1.0673        | 0.9   | 150  | 0.9405          |
| 0.7058        | 1.2   | 200  | 1.0023          |
| 0.5501        | 1.5   | 250  | 1.0274          |
| 0.5649        | 1.8   | 300  | 0.9887          |
| 0.4972        | 2.1   | 350  | 1.0855          |
| 0.2934        | 2.4   | 400  | 1.1109          |
| 0.2999        | 2.69  | 450  | 1.0877          |
| 0.2907        | 2.99  | 500  | 1.0879          |
| 0.1533        | 3.29  | 550  | 1.2041          |
| 0.1553        | 3.59  | 600  | 1.1832          |
| 0.1681        | 3.89  | 650  | 1.1806          |
| 0.107         | 4.19  | 700  | 1.2764          |
| 0.0914        | 4.49  | 750  | 1.2541          |
| 0.1001        | 4.79  | 800  | 1.2589          |
| 0.0816        | 5.09  | 850  | 1.3118          |
| 0.0548        | 5.39  | 900  | 1.3473          |
| 0.068         | 5.69  | 950  | 1.2907          |
| 0.0615        | 5.99  | 1000 | 1.3007          |
| 0.0358        | 6.29  | 1050 | 1.4036          |
| 0.0409        | 6.59  | 1100 | 1.3794          |
| 0.0473        | 6.89  | 1150 | 1.3592          |
| 0.0413        | 7.19  | 1200 | 1.4133          |
| 0.0438        | 7.49  | 1250 | 1.3690          |
| 0.034         | 7.78  | 1300 | 1.3665          |
| 0.0307        | 8.08  | 1350 | 1.4268          |
| 0.0211        | 8.38  | 1400 | 1.4637          |
| 0.0302        | 8.68  | 1450 | 1.4456          |
| 0.0288        | 8.98  | 1500 | 1.4584          |
| 0.0232        | 9.28  | 1550 | 1.4431          |
| 0.017         | 9.58  | 1600 | 1.4756          |
| 0.02          | 9.88  | 1650 | 1.4988          |
| 0.0207        | 10.18 | 1700 | 1.5071          |
| 0.0182        | 10.48 | 1750 | 1.4956          |
| 0.0155        | 10.78 | 1800 | 1.5102          |
| 0.0163        | 11.08 | 1850 | 1.5207          |
| 0.0122        | 11.38 | 1900 | 1.5392          |
| 0.0156        | 11.68 | 1950 | 1.5124          |
| 0.0149        | 11.98 | 2000 | 1.5184          |
| 0.0128        | 12.28 | 2050 | 1.5435          |
| 0.0107        | 12.57 | 2100 | 1.5686          |
| 0.0118        | 12.87 | 2150 | 1.5301          |
| 0.0094        | 13.17 | 2200 | 1.5828          |
| 0.0173        | 13.47 | 2250 | 1.5810          |


### Framework versions

- Transformers 4.29.2
- Pytorch 1.10.0+cu111
- Datasets 2.5.1
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt2-large-NaturalQuestions_2000-ep20", "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-large-NaturalQuestions\_2000-ep20
======================================


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


* Loss: 1.5184


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-05
* train\_batch\_size: 12
* eval\_batch\_size: 24
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 12
* eval\_batch\_size: 24
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.13.3
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: 2e-05
* train\_batch\_size: 12
* eval\_batch\_size: 24
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.13.3