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# distilbert-base-uncased-finetuned-with-spanish-tweets-clf

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0580
- Accuracy: 0.5701
- F1: 0.5652
- Precision: 0.5666
- Recall: 0.5642

## 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: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.0643        | 1.0   | 543  | 1.0457          | 0.4423   | 0.2761 | 0.5104    | 0.3712 |
| 0.9754        | 2.0   | 1086 | 0.9700          | 0.5155   | 0.4574 | 0.5190    | 0.4712 |
| 0.8145        | 3.0   | 1629 | 0.9691          | 0.5556   | 0.5544 | 0.5616    | 0.5506 |
| 0.6318        | 4.0   | 2172 | 1.0580          | 0.5701   | 0.5652 | 0.5666    | 0.5642 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["dataset"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "distilbert-base-uncased-finetuned-with-spanish-tweets-clf", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "dataset", "type": "dataset", "config": "60-20-20", "split": "dev", "args": "60-20-20"}, "metrics": [{"type": "accuracy", "value": 0.5701451278507257, "name": "Accuracy"}, {"type": "f1", "value": 0.5651604812495131, "name": "F1"}, {"type": "precision", "value": 0.5665667380442541, "name": "Precision"}, {"type": "recall", "value": 0.5641613027059359, "name": "Recall"}]}]}]}
transformers pytorch distilbert text-classification generated_from_trainer dataset:dataset license:apache-2.0 model-index autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 

distilbert-base-uncased-finetuned-with-spanish-tweets-clf
=========================================================


This model is a fine-tuned version of distilbert-base-uncased on the dataset dataset.
It achieves the following results on the evaluation set:


* Loss: 1.0580
* Accuracy: 0.5701
* F1: 0.5652
* Precision: 0.5666
* Recall: 0.5642


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: 8
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4.0


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1
* Datasets 2.8.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4.0 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4.0 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4.0### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1
* Datasets 2.8.0
* Tokenizers 0.13.2