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# petro-twitter-assistant-30ep

This model is a fine-tuned version of [flax-community/gpt-2-spanish](https://huggingface.co/flax-community/gpt-2-spanish) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.8837

## 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: 0.0001
- train_batch_size: 20
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.123         | 2.3   | 1000  | 3.0761          |
| 2.8048        | 4.6   | 2000  | 3.0394          |
| 2.5904        | 6.9   | 3000  | 3.0743          |
| 2.3804        | 9.2   | 4000  | 3.2378          |
| 2.1736        | 11.49 | 5000  | 3.4025          |
| 1.9736        | 13.79 | 6000  | 3.6284          |
| 1.779         | 16.09 | 7000  | 3.9806          |
| 1.5993        | 18.39 | 8000  | 4.2559          |
| 1.4584        | 20.69 | 9000  | 4.4938          |
| 1.3492        | 22.99 | 10000 | 4.6608          |
| 1.2701        | 25.29 | 11000 | 4.8302          |
| 1.2309        | 27.59 | 12000 | 4.8696          |
| 1.2161        | 29.89 | 13000 | 4.8837          |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"language": ["es"], "tags": ["generated_from_trainer"], "datasets": ["jhonparra18/petro-tweets"], "widget": [{"text": "Opino que mi gobierno es"}], "model-index": [{"name": "petro-twitter-assistant-30ep", "results": []}]}
transformers pytorch gpt2 text-generation generated_from_trainer es dataset:jhonparra18/petro-tweets autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #es #dataset-jhonparra18/petro-tweets #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

petro-twitter-assistant-30ep
============================


This model is a fine-tuned version of flax-community/gpt-2-spanish on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 4.8837


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: 0.0001
* train\_batch\_size: 20
* eval\_batch\_size: 20
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 40
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 30
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 20
* eval\_batch\_size: 20
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 40
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #es #dataset-jhonparra18/petro-tweets #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 20
* eval\_batch\_size: 20
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 40
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #es #dataset-jhonparra18/petro-tweets #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 20
* eval\_batch\_size: 20
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 40
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 30
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1