
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# electra-base-gen-finetuned-amazon-review

This model is a fine-tuned version of [mrm8488/electricidad-base-generator](https://huggingface.co/mrm8488/electricidad-base-generator) on the amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8030
- Accuracy: 0.5024
- F1: 0.5063
- Precision: 0.5121
- Recall: 0.5024

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Accuracy | F1     | Validation Loss | Precision | Recall |
|:-------------:|:-----:|:----:|:--------:|:------:|:---------------:|:---------:|:------:|
| 0.5135        | 1.0   | 1000 | 0.4886   | 0.4929 | 1.6580          | 0.5077    | 0.4886 |
| 0.4138        | 2.0   | 2000 | 0.5044   | 0.5093 | 1.7951          | 0.5183    | 0.5044 |
| 0.4244        | 3.0   | 3000 | 0.5022   | 0.5068 | 1.8108          | 0.5141    | 0.5022 |
| 0.4231        | 6.0   | 6000 | 1.7636   | 0.4972 | 0.5018          | 0.5092    | 0.4972 |
| 0.3574        | 7.0   | 7000 | 1.8030   | 0.5024 | 0.5063          | 0.5121    | 0.5024 |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "datasets": ["amazon_reviews_multi"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "electra-base-gen-finetuned-amazon-review", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "amazon_reviews_multi", "type": "amazon_reviews_multi", "args": "es"}, "metrics": [{"type": "accuracy", "value": 0.5024, "name": "Accuracy"}, {"type": "f1", "value": 0.5063190059782597, "name": "F1"}, {"type": "precision", "value": 0.5121183330982292, "name": "Precision"}, {"type": "recall", "value": 0.5024, "name": "Recall"}]}]}]}
transformers pytorch tensorboard electra text-classification generated_from_trainer dataset:amazon_reviews_multi model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #electra #text-classification #generated_from_trainer #dataset-amazon_reviews_multi #model-index #autotrain_compatible #endpoints_compatible #region-us 

electra-base-gen-finetuned-amazon-review
========================================


This model is a fine-tuned version of mrm8488/electricidad-base-generator on the amazon\_reviews\_multi dataset.
It achieves the following results on the evaluation set:


* Loss: 1.8030
* Accuracy: 0.5024
* F1: 0.5063
* Precision: 0.5121
* Recall: 0.5024


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: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7


### Training results



### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.17.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.17.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #electra #text-classification #generated_from_trainer #dataset-amazon_reviews_multi #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.17.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #electra #text-classification #generated_from_trainer #dataset-amazon_reviews_multi #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7### Training results### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.17.0
* Tokenizers 0.10.3