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# distilbert-base-multilingual-cased-finetuned-with-spanish-tweets-clf

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4692
- Accuracy: 0.6006
- F1: 0.5981
- Precision: 0.6009
- Recall: 0.5963

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.0168        | 1.0   | 543  | 0.9144          | 0.5563   | 0.5012 | 0.5240    | 0.5251 |
| 0.8197        | 2.0   | 1086 | 0.9133          | 0.5764   | 0.5476 | 0.5815    | 0.5462 |
| 0.5574        | 3.0   | 1629 | 1.0629          | 0.6151   | 0.6150 | 0.6227    | 0.6112 |
| 0.3487        | 4.0   | 2172 | 1.4692          | 0.6006   | 0.5981 | 0.6009    | 0.5963 |


### 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-multilingual-cased-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": 0.6005528680027643, "name": "Accuracy"}, {"type": "f1", "value": 0.5980973383983778, "name": "F1"}, {"type": "precision", "value": 0.6008849518067042, "name": "Precision"}, {"type": "recall", "value": 0.5962561389203832, "name": "Recall"}]}]}]}
transformers pytorch distilbert text-classification generated_from_trainer dataset:dataset license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

distilbert-base-multilingual-cased-finetuned-with-spanish-tweets-clf
====================================================================


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


* Loss: 1.4692
* Accuracy: 0.6006
* F1: 0.5981
* Precision: 0.6009
* Recall: 0.5963


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 #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 #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