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# gpt2-ear_1-hs_cn_decay

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: 0.5369

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 74.0475       | 0.02  | 10   | 72.6562         |
| 45.5005       | 0.04  | 20   | 34.4060         |
| 10.921        | 0.06  | 30   | 11.2525         |
| 2.7976        | 0.08  | 40   | 4.4890          |
| 0.0358        | 0.1   | 50   | 2.1808          |
| -1.4128       | 0.12  | 60   | 1.1029          |
| -1.7651       | 0.14  | 70   | 0.9684          |
| -1.9542       | 0.16  | 80   | 0.7785          |
| -2.1013       | 0.18  | 90   | 0.6533          |
| -2.14         | 0.2   | 100  | 0.6666          |
| -2.1001       | 0.22  | 110  | 0.6334          |
| -2.1169       | 0.24  | 120  | 0.5926          |
| -2.1216       | 0.26  | 130  | 0.5903          |
| -2.1191       | 0.28  | 140  | 0.5741          |
| -2.1319       | 0.3   | 150  | 0.5702          |
| -2.122        | 0.32  | 160  | 0.5679          |
| -2.0754       | 0.34  | 170  | 0.5671          |
| -2.06         | 0.36  | 180  | 0.5630          |
| -2.0477       | 0.38  | 190  | 0.5591          |
| -2.0569       | 0.4   | 200  | 0.5546          |
| -1.9666       | 0.42  | 210  | 0.5513          |
| -1.9673       | 0.44  | 220  | 0.5558          |
| -2.0044       | 0.46  | 230  | 0.5560          |
| -1.9923       | 0.48  | 240  | 0.5507          |
| -1.9056       | 0.5   | 250  | 0.5494          |
| -1.9658       | 0.52  | 260  | 0.5498          |
| -1.9104       | 0.54  | 270  | 0.5474          |
| -1.8967       | 0.56  | 280  | 0.5459          |
| -1.8759       | 0.58  | 290  | 0.5458          |
| -1.8432       | 0.6   | 300  | 0.5477          |
| -1.835        | 0.62  | 310  | 0.5446          |
| -1.7823       | 0.64  | 320  | 0.5448          |
| -1.8058       | 0.66  | 330  | 0.5412          |
| -1.8138       | 0.68  | 340  | 0.5375          |
| -1.7656       | 0.7   | 350  | 0.5385          |
| -1.7174       | 0.72  | 360  | 0.5376          |
| -1.7461       | 0.74  | 370  | 0.5365          |
| -1.7145       | 0.76  | 380  | 0.5342          |
| -1.6737       | 0.78  | 390  | 0.5326          |
| -1.7162       | 0.8   | 400  | 0.5342          |
| -1.6792       | 0.82  | 410  | 0.5361          |
| -1.6783       | 0.84  | 420  | 0.5369          |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.11.0+cu113
- Datasets 2.6.1
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt2-ear_1-hs_cn_decay", "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-ear\_1-hs\_cn\_decay
=========================


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


* Loss: 0.5369


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 4.24.0
* Pytorch 1.11.0+cu113
* Datasets 2.6.1
* Tokenizers 0.12.1



### 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 4.24.0
* Pytorch 1.11.0+cu113
* Datasets 2.6.1
* Tokenizers 0.12.1
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 4.24.0
* Pytorch 1.11.0+cu113
* Datasets 2.6.1
* Tokenizers 0.12.1
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 4.24.0
* Pytorch 1.11.0+cu113
* Datasets 2.6.1
* Tokenizers 0.12.1