


# clasificador-muchocine

This model is a fine-tuned version of [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on the 'muchocine' dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3389
- Accuracy: 0.4671

## Model description

This model predicts a 1-5 star_rating for a movie based on a short review in Spanish.


## Training and evaluation data

The model uses the train split of the 'muchocine' dataset, containing 3,872 reviews.

## Training procedure

The original dataset was randomized and subsequently split into a training set (80%) and a testing set (20%).

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-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
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 388  | 1.2937          | 0.4335   |
| 1.4261        | 2.0   | 776  | 1.2515          | 0.4839   |
| 1.0492        | 3.0   | 1164 | 1.3389          | 0.4671   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
{"language": ["es"], "tags": ["classification", "generated_from_trainer"], "datasets": ["muchocine"], "metrics": ["accuracy"], "model-index": [{"name": "clasificador-muchocine", "results": []}]}
transformers pytorch electra text-classification classification generated_from_trainer es dataset:muchocine autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #electra #text-classification #classification #generated_from_trainer #es #dataset-muchocine #autotrain_compatible #endpoints_compatible #region-us 

clasificador-muchocine
======================


This model is a fine-tuned version of mrm8488/electricidad-base-discriminator on the 'muchocine' dataset.
It achieves the following results on the evaluation set:


* Loss: 1.3389
* Accuracy: 0.4671


Model description
-----------------


This model predicts a 1-5 star\_rating for a movie based on a short review in Spanish.


Training and evaluation data
----------------------------


The model uses the train split of the 'muchocine' dataset, containing 3,872 reviews.


Training procedure
------------------


The original dataset was randomized and subsequently split into a training set (80%) and a testing set (20%).


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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
* num\_epochs: 3.0


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #electra #text-classification #classification #generated_from_trainer #es #dataset-muchocine #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #electra #text-classification #classification #generated_from_trainer #es #dataset-muchocine #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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
* num\_epochs: 3.0### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2