
<!-- 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_trinity_2_4_3e-5_lp5_nb5

This model is a fine-tuned version of [skt/kogpt2-base-v2](https://huggingface.co/skt/kogpt2-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0291

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.5765        | 0.05  | 1000  | 4.1247          |
| 3.19          | 0.09  | 2000  | 4.0578          |
| 3.1177        | 0.14  | 3000  | 4.0708          |
| 3.1116        | 0.19  | 4000  | 4.0654          |
| 3.0777        | 0.24  | 5000  | 4.0857          |
| 3.1105        | 0.28  | 6000  | 4.1127          |
| 3.1018        | 0.33  | 7000  | 4.1410          |
| 3.0728        | 0.38  | 8000  | 4.1834          |
| 3.1248        | 0.42  | 9000  | 4.2058          |
| 3.1035        | 0.47  | 10000 | 4.2048          |
| 3.0943        | 0.52  | 11000 | 4.1892          |
| 3.0724        | 0.57  | 12000 | 4.2063          |
| 3.0517        | 0.61  | 13000 | 4.1923          |
| 3.0372        | 0.66  | 14000 | 4.2112          |
| 3.0235        | 0.71  | 15000 | 4.2043          |
| 3.0329        | 0.76  | 16000 | 4.1630          |
| 3.0171        | 0.8   | 17000 | 4.1631          |
| 2.9997        | 0.85  | 18000 | 4.1563          |
| 2.9913        | 0.9   | 19000 | 4.1616          |
| 2.9579        | 0.94  | 20000 | 4.1494          |
| 2.9576        | 0.99  | 21000 | 4.1367          |
| 2.7461        | 1.04  | 22000 | 4.1593          |
| 2.7637        | 1.09  | 23000 | 4.1453          |
| 2.741         | 1.13  | 24000 | 4.1624          |
| 2.7514        | 1.18  | 25000 | 4.1357          |
| 2.755         | 1.23  | 26000 | 4.1524          |
| 2.7365        | 1.27  | 27000 | 4.1399          |
| 2.7356        | 1.32  | 28000 | 4.1285          |
| 2.7386        | 1.37  | 29000 | 4.1286          |
| 2.7489        | 1.42  | 30000 | 4.1231          |
| 2.7518        | 1.46  | 31000 | 4.1104          |
| 2.7317        | 1.51  | 32000 | 4.1202          |
| 2.7378        | 1.56  | 33000 | 4.1132          |
| 2.7309        | 1.6   | 34000 | 4.1047          |
| 2.7791        | 1.65  | 35000 | 4.0976          |
| 2.7427        | 1.7   | 36000 | 4.0874          |
| 2.7184        | 1.75  | 37000 | 4.0953          |
| 2.7107        | 1.79  | 38000 | 4.0963          |
| 2.7122        | 1.84  | 39000 | 4.0841          |
| 2.7172        | 1.89  | 40000 | 4.0852          |
| 2.7126        | 1.94  | 41000 | 4.0632          |
| 2.7063        | 1.98  | 42000 | 4.0643          |
| 2.5311        | 2.03  | 43000 | 4.0848          |
| 2.4496        | 2.08  | 44000 | 4.0943          |
| 2.4597        | 2.12  | 45000 | 4.0799          |
| 2.4472        | 2.17  | 46000 | 4.0802          |
| 2.4628        | 2.22  | 47000 | 4.0880          |
| 2.4508        | 2.27  | 48000 | 4.0791          |
| 2.4743        | 2.31  | 49000 | 4.0765          |
| 2.4692        | 2.36  | 50000 | 4.0739          |
| 2.4651        | 2.41  | 51000 | 4.0690          |
| 2.4885        | 2.45  | 52000 | 4.0723          |
| 2.5023        | 2.5   | 53000 | 4.0675          |
| 2.4651        | 2.55  | 54000 | 4.0649          |
| 2.4774        | 2.6   | 55000 | 4.0695          |
| 2.4717        | 2.64  | 56000 | 4.0559          |
| 2.4856        | 2.69  | 57000 | 4.0512          |
| 2.4572        | 2.74  | 58000 | 4.0473          |
| 2.486         | 2.79  | 59000 | 4.0438          |
| 2.449         | 2.83  | 60000 | 4.0385          |
| 2.456         | 2.88  | 61000 | 4.0355          |
| 2.4802        | 2.93  | 62000 | 4.0378          |
| 2.4635        | 2.97  | 63000 | 4.0308          |
| 2.3742        | 3.02  | 64000 | 4.0488          |
| 2.2371        | 3.07  | 65000 | 4.0579          |
| 2.2496        | 3.12  | 66000 | 4.0630          |
| 2.2758        | 3.16  | 67000 | 4.0516          |
| 2.2489        | 3.21  | 68000 | 4.0585          |
| 2.2374        | 3.26  | 69000 | 4.0715          |
| 2.2862        | 3.3   | 70000 | 4.0507          |
| 2.2502        | 3.35  | 71000 | 4.0512          |
| 2.238         | 3.4   | 72000 | 4.0545          |
| 2.2407        | 3.45  | 73000 | 4.0459          |
| 2.2529        | 3.49  | 74000 | 4.0452          |
| 2.2453        | 3.54  | 75000 | 4.0459          |
| 2.2314        | 3.59  | 76000 | 4.0416          |
| 2.2408        | 3.63  | 77000 | 4.0379          |
| 2.2497        | 3.68  | 78000 | 4.0348          |
| 2.2475        | 3.73  | 79000 | 4.0374          |
| 2.2376        | 3.78  | 80000 | 4.0319          |
| 2.244         | 3.82  | 81000 | 4.0331          |
| 2.2611        | 3.87  | 82000 | 4.0306          |
| 2.237         | 3.92  | 83000 | 4.0301          |
| 2.2337        | 3.97  | 84000 | 4.0291          |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.9.0+cu102
- Datasets 2.8.0
- Tokenizers 0.13.2

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt_trinity_2_4_3e-5_lp5_nb5", "results": []}]}
transformers pytorch tensorboard gpt2 text-generation generated_from_trainer license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

gpt\_trinity\_2\_4\_3e-5\_lp5\_nb5
==================================


This model is a fine-tuned version of skt/kogpt2-base-v2 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 4.0291


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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 4.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.25.1
* Pytorch 1.9.0+cu102
* Datasets 2.8.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 4.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.9.0+cu102
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-cc-by-nc-sa-4.0 #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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 4.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.9.0+cu102
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-cc-by-nc-sa-4.0 #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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 4.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.25.1
* Pytorch 1.9.0+cu102
* Datasets 2.8.0
* Tokenizers 0.13.2