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# gpt2-sweep

This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0808
- Accuracy: 0.8556

## 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: 2.294477077303931e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 2.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.4827        | 0.19  | 1000  | 2.4565          | 0.8520   |
| 2.6468        | 0.37  | 2000  | 2.3303          | 0.8530   |
| 2.5106        | 0.56  | 3000  | 2.2487          | 0.8537   |
| 2.0732        | 0.74  | 4000  | 2.2020          | 0.8541   |
| 2.159         | 0.93  | 5000  | 2.1594          | 0.8545   |
| 1.856         | 1.12  | 6000  | 2.1518          | 0.8548   |
| 1.9138        | 1.3   | 7000  | 2.1261          | 0.8551   |
| 1.8055        | 1.49  | 8000  | 2.1126          | 0.8552   |
| 2.0385        | 1.67  | 9000  | 2.1008          | 0.8554   |
| 1.9648        | 1.86  | 10000 | 2.0858          | 0.8555   |


### Framework versions

- Transformers 4.26.0
- Pytorch 2.0.0+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "gpt2-sweep", "results": []}]}
transformers pytorch safetensors gpt2 text-generation generated_from_trainer license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

gpt2-sweep
==========


This model is a fine-tuned version of gpt2-large on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.0808
* Accuracy: 0.8556


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: 2.294477077303931e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 2.0


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 2.0.0+cu117
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2.294477077303931e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 2.0 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 2.0.0+cu117
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #safetensors #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: 2.294477077303931e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 2.0 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 2.0.0+cu117
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #safetensors #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: 2.294477077303931e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 2.0### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 2.0.0+cu117
* Datasets 2.9.0
* Tokenizers 0.13.2