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# output

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: 0.5751
- Accuracy: 0.0021

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2205        | 1.25  | 315  | 0.8209          | 0.0010   |
| 0.813         | 2.51  | 630  | 0.7684          | 0.0009   |
| 0.7645        | 3.76  | 945  | 0.7393          | 0.0008   |
| 0.7249        | 5.02  | 1260 | 0.6980          | 0.0007   |
| 0.6832        | 6.27  | 1575 | 0.6646          | 0.0003   |
| 0.6426        | 7.53  | 1890 | 0.6371          | 0.0019   |
| 0.6034        | 8.78  | 2205 | 0.6041          | 0.0020   |
| 0.564         | 10.04 | 2520 | 0.5897          | 0.0018   |
| 0.5253        | 11.29 | 2835 | 0.5857          | 0.0018   |
| 0.4961        | 12.55 | 3150 | 0.5771          | 0.0017   |
| 0.4752        | 13.8  | 3465 | 0.5751          | 0.0021   |


### 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": "output", "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 

output
======


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


* Loss: 0.5751
* Accuracy: 0.0021


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: 15


### 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: 15 ### 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: 15 ### Training results ### Framework versions


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