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# ES-ENG-mBERT-sentiment

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on a Custom dataset.

The best model (stopped after 14 epochs) achieves the following results on the evaluation set:
- Loss: 0.8110
- Accuracy: 0.6307
- F1: 0.6298
- Precision: 0.6291
- Recall: 0.6307

## Intended uses & limitations

Note that commercial use with this model is prohibited.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-06
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.063         | 1.0   | 208  | 0.9989          | 0.4731   | 0.4044 | 0.4885    | 0.4731 |
| 0.9664        | 2.0   | 416  | 0.9144          | 0.5262   | 0.4845 | 0.5270    | 0.5262 |
| 0.9067        | 3.0   | 624  | 0.8648          | 0.5896   | 0.5844 | 0.5935    | 0.5896 |
| 0.8572        | 4.0   | 832  | 0.8294          | 0.6065   | 0.5984 | 0.6102    | 0.6065 |
| 0.8168        | 5.0   | 1040 | 0.8101          | 0.6107   | 0.6092 | 0.6119    | 0.6107 |
| 0.7897        | 6.0   | 1248 | 0.8213          | 0.6074   | 0.6015 | 0.6018    | 0.6074 |
| 0.7568        | 7.0   | 1456 | 0.7992          | 0.6194   | 0.6181 | 0.6176    | 0.6194 |
| 0.7465        | 8.0   | 1664 | 0.8089          | 0.6246   | 0.6183 | 0.6206    | 0.6246 |
| 0.7223        | 9.0   | 1872 | 0.7988          | 0.6236   | 0.6214 | 0.6207    | 0.6236 |
| 0.7045        | 10.0  | 2080 | 0.8390          | 0.6165   | 0.6080 | 0.6126    | 0.6165 |
| 0.6888        | 11.0  | 2288 | 0.8042          | 0.6291   | 0.6260 | 0.6257    | 0.6291 |
| 0.671         | 12.0  | 2496 | 0.8088          | 0.6239   | 0.6212 | 0.6216    | 0.6239 |
| 0.6543        | 13.0  | 2704 | 0.8104          | 0.6256   | 0.6227 | 0.6216    | 0.6256 |
| 0.6409        | 14.0  | 2912 | 0.8110          | 0.6307   | 0.6298 | 0.6291    | 0.6307 |
| 0.6275        | 15.0  | 3120 | 0.8127          | 0.6298   | 0.6292 | 0.6299    | 0.6298 |
| 0.6176        | 16.0  | 3328 | 0.8334          | 0.6252   | 0.6217 | 0.6206    | 0.6252 |
| 0.6096        | 17.0  | 3536 | 0.8331          | 0.6256   | 0.6210 | 0.6210    | 0.6256 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "ES-ENG-mBERT-sentiment", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer license:cc-by-nc-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #region-us 

ES-ENG-mBERT-sentiment
======================


This model is a fine-tuned version of bert-base-multilingual-cased on a Custom dataset.


The best model (stopped after 14 epochs) achieves the following results on the evaluation set:


* Loss: 0.8110
* Accuracy: 0.6307
* F1: 0.6298
* Precision: 0.6291
* Recall: 0.6307


Intended uses & limitations
---------------------------


Note that commercial use with this model is prohibited.


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


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-06
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-06
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-06
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3