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# gpt2-no_ear-loto_muslim

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: 0.5300

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 73.4971       | 0.03  | 10   | 65.0370         |
| 31.3006       | 0.06  | 20   | 18.3819         |
| 11.2569       | 0.08  | 30   | 7.1196          |
| 3.7539        | 0.11  | 40   | 3.1582          |
| 1.8809        | 0.14  | 50   | 1.3415          |
| 1.0793        | 0.17  | 60   | 1.0276          |
| 0.905         | 0.2   | 70   | 0.7964          |
| 0.6987        | 0.23  | 80   | 0.7864          |
| 0.6243        | 0.25  | 90   | 0.7058          |
| 0.8346        | 0.28  | 100  | 0.6183          |
| 0.6377        | 0.31  | 110  | 0.6017          |
| 0.6088        | 0.34  | 120  | 0.5991          |
| 0.6074        | 0.37  | 130  | 0.5934          |
| 0.654         | 0.4   | 140  | 0.5844          |
| 0.6306        | 0.42  | 150  | 0.5815          |
| 0.6793        | 0.45  | 160  | 0.5951          |
| 0.6046        | 0.48  | 170  | 0.5731          |
| 0.6794        | 0.51  | 180  | 0.5730          |
| 0.6727        | 0.54  | 190  | 0.5682          |
| 0.5556        | 0.57  | 200  | 0.5611          |
| 0.6247        | 0.59  | 210  | 0.5570          |
| 0.6           | 0.62  | 220  | 0.5563          |
| 0.5464        | 0.65  | 230  | 0.5518          |
| 0.547         | 0.68  | 240  | 0.5516          |
| 0.4901        | 0.71  | 250  | 0.5468          |
| 0.5852        | 0.74  | 260  | 0.5472          |
| 0.5393        | 0.76  | 270  | 0.5459          |
| 0.5324        | 0.79  | 280  | 0.5468          |
| 0.5862        | 0.82  | 290  | 0.5438          |
| 0.5508        | 0.85  | 300  | 0.5404          |
| 0.6012        | 0.88  | 310  | 0.5368          |
| 0.525         | 0.91  | 320  | 0.5358          |
| 0.5764        | 0.93  | 330  | 0.5336          |
| 0.5239        | 0.96  | 340  | 0.5290          |
| 0.5902        | 0.99  | 350  | 0.5294          |
| 0.5059        | 1.02  | 360  | 0.5335          |
| 0.5069        | 1.05  | 370  | 0.5300          |


### Framework versions

- Transformers 4.28.0
- Pytorch 1.11.0+cu113
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt2-no_ear-loto_muslim", "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-no\_ear-loto\_muslim
=========================


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


* Loss: 0.5300


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 0.13.3



### 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 0.13.3
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: 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 0.13.3