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# js-fake-bach-epochs20

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5800
- Accuracy: 0.0015

## 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: 0.0006058454513356471
- train_batch_size: 16
- eval_batch_size: 32
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2488        | 1.25  | 315  | 0.8243          | 0.0009   |
| 0.8134        | 2.51  | 630  | 0.7738          | 0.0010   |
| 0.7677        | 3.76  | 945  | 0.7396          | 0.0002   |
| 0.7314        | 5.02  | 1260 | 0.7088          | 0.0006   |
| 0.692         | 6.27  | 1575 | 0.6734          | 0.0009   |
| 0.6545        | 7.53  | 1890 | 0.6414          | 0.0010   |
| 0.6175        | 8.78  | 2205 | 0.6071          | 0.0008   |
| 0.5782        | 10.04 | 2520 | 0.5945          | 0.0017   |
| 0.5385        | 11.29 | 2835 | 0.5838          | 0.0009   |
| 0.5026        | 12.55 | 3150 | 0.5722          | 0.0013   |
| 0.4694        | 13.8  | 3465 | 0.5676          | 0.0011   |
| 0.4389        | 15.06 | 3780 | 0.5713          | 0.0011   |
| 0.4083        | 16.31 | 4095 | 0.5761          | 0.0015   |
| 0.389         | 17.57 | 4410 | 0.5790          | 0.0015   |
| 0.3771        | 18.82 | 4725 | 0.5800          | 0.0015   |


### Framework versions

- Transformers 4.29.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "js-fake-bach-epochs20", "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 

js-fake-bach-epochs20
=====================


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


* Loss: 0.5800
* Accuracy: 0.0015


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: 0.0006058454513356471
* train\_batch\_size: 16
* eval\_batch\_size: 32
* seed: 1
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.01
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.29.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0006058454513356471
* train\_batch\_size: 16
* eval\_batch\_size: 32
* seed: 1
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.01
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.29.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* 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: 0.0006058454513356471
* train\_batch\_size: 16
* eval\_batch\_size: 32
* seed: 1
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.01
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.29.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3