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# gpt2-large-NaturalQuestions_4000-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: 1.2404

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2669        | 0.15  | 50   | 1.0266          |
| 1.091         | 0.3   | 100  | 0.9900          |
| 1.0277        | 0.45  | 150  | 0.9562          |
| 1.0095        | 0.6   | 200  | 0.9515          |
| 1.0311        | 0.75  | 250  | 0.9247          |
| 0.9533        | 0.9   | 300  | 0.9114          |
| 0.8352        | 1.05  | 350  | 0.9219          |
| 0.543         | 1.2   | 400  | 0.9551          |
| 0.5364        | 1.35  | 450  | 0.9691          |
| 0.5246        | 1.5   | 500  | 0.9491          |
| 0.5454        | 1.65  | 550  | 0.9552          |
| 0.5586        | 1.8   | 600  | 0.9510          |
| 0.5593        | 1.95  | 650  | 0.9694          |
| 0.3849        | 2.1   | 700  | 1.0554          |
| 0.2775        | 2.25  | 750  | 1.0372          |
| 0.2847        | 2.4   | 800  | 1.0488          |
| 0.2964        | 2.54  | 850  | 1.0312          |
| 0.2938        | 2.69  | 900  | 1.0604          |
| 0.288         | 2.84  | 950  | 1.0605          |
| 0.308         | 2.99  | 1000 | 1.0322          |
| 0.1557        | 3.14  | 1050 | 1.1383          |
| 0.1586        | 3.29  | 1100 | 1.1386          |
| 0.1696        | 3.44  | 1150 | 1.1489          |
| 0.1665        | 3.59  | 1200 | 1.1383          |
| 0.1653        | 3.74  | 1250 | 1.1548          |
| 0.1791        | 3.89  | 1300 | 1.1275          |
| 0.1519        | 4.04  | 1350 | 1.1838          |
| 0.0953        | 4.19  | 1400 | 1.2258          |
| 0.0964        | 4.34  | 1450 | 1.2286          |
| 0.0967        | 4.49  | 1500 | 1.2159          |
| 0.1023        | 4.64  | 1550 | 1.1961          |
| 0.1107        | 4.79  | 1600 | 1.1961          |
| 0.1015        | 4.94  | 1650 | 1.2439          |
| 0.0792        | 5.09  | 1700 | 1.2571          |
| 0.0611        | 5.24  | 1750 | 1.2737          |
| 0.0654        | 5.39  | 1800 | 1.2909          |
| 0.0621        | 5.54  | 1850 | 1.2612          |
| 0.0707        | 5.69  | 1900 | 1.2836          |
| 0.0627        | 5.84  | 1950 | 1.2889          |
| 0.0842        | 5.99  | 2000 | 1.2404          |
| 0.0485        | 6.14  | 2050 | 1.3126          |
| 0.0399        | 6.29  | 2100 | 1.3524          |
| 0.0501        | 6.44  | 2150 | 1.2900          |
| 0.0474        | 6.59  | 2200 | 1.2991          |
| 0.048         | 6.74  | 2250 | 1.3290          |


### 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_4000-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\_4000-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: 1.2404


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