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# ES-ENG-mDeBERTa-sentiment

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on a Custom dataset.

The best model (stopped after 20 epochs) achieves the following results on the evaluation set:
- Loss:0.7549
- Accuracy: 0.6806
- F1: 0.6783
- Precision: 0.6775
- Recall: 0.6806

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.0833        | 1.0   | 208  | 1.0218          | 0.3835   | 0.2413 | 0.4619    | 0.3835 |
| 0.9826        | 2.0   | 416  | 0.9220          | 0.5673   | 0.5524 | 0.5583    | 0.5673 |
| 0.8951        | 3.0   | 624  | 0.8435          | 0.5916   | 0.5836 | 0.5853    | 0.5916 |
| 0.8377        | 4.0   | 832  | 0.8200          | 0.5994   | 0.5916 | 0.5931    | 0.5994 |
| 0.8083        | 5.0   | 1040 | 0.8110          | 0.5977   | 0.5960 | 0.5957    | 0.5977 |
| 0.7854        | 6.0   | 1248 | 0.8009          | 0.5994   | 0.5943 | 0.5916    | 0.5994 |
| 0.7699        | 7.0   | 1456 | 0.7919          | 0.6084   | 0.6065 | 0.6055    | 0.6084 |
| 0.7489        | 8.0   | 1664 | 0.7827          | 0.6230   | 0.6164 | 0.6192    | 0.6230 |
| 0.7323        | 9.0   | 1872 | 0.7739          | 0.6272   | 0.6251 | 0.6246    | 0.6272 |
| 0.7162        | 10.0  | 2080 | 0.7725          | 0.6408   | 0.6332 | 0.6351    | 0.6408 |
| 0.6958        | 11.0  | 2288 | 0.7636          | 0.6414   | 0.6393 | 0.6383    | 0.6414 |
| 0.6816        | 12.0  | 2496 | 0.7582          | 0.6495   | 0.6491 | 0.6516    | 0.6495 |
| 0.6706        | 13.0  | 2704 | 0.7492          | 0.6628   | 0.6607 | 0.6595    | 0.6628 |
| 0.6569        | 14.0  | 2912 | 0.7554          | 0.6586   | 0.6580 | 0.6579    | 0.6586 |
| 0.6422        | 15.0  | 3120 | 0.7525          | 0.6676   | 0.6661 | 0.6667    | 0.6676 |
| 0.6408        | 16.0  | 3328 | 0.7527          | 0.6660   | 0.6658 | 0.6669    | 0.6660 |
| 0.6273        | 17.0  | 3536 | 0.7483          | 0.6712   | 0.6700 | 0.6710    | 0.6712 |
| 0.6186        | 18.0  | 3744 | 0.7531          | 0.6748   | 0.6731 | 0.6727    | 0.6748 |
| 0.6107        | 19.0  | 3952 | 0.7482          | 0.6799   | 0.6786 | 0.6782    | 0.6799 |
| 0.6055        | 20.0  | 4160 | 0.7549          | 0.6806   | 0.6783 | 0.6775    | 0.6806 |
| 0.6026        | 21.0  | 4368 | 0.7574          | 0.6725   | 0.6719 | 0.6733    | 0.6725 |
| 0.5906        | 22.0  | 4576 | 0.7587          | 0.6728   | 0.6721 | 0.6723    | 0.6728 |
| 0.5888        | 23.0  | 4784 | 0.7621          | 0.6761   | 0.6756 | 0.6758    | 0.6761 |


### 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-mDeBERTa-sentiment", "results": []}]}
transformers pytorch deberta-v2 text-classification generated_from_trainer license:cc-by-nc-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #deberta-v2 #text-classification #generated_from_trainer #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #region-us 

ES-ENG-mDeBERTa-sentiment
=========================


This model is a fine-tuned version of microsoft/mdeberta-v3-base on a Custom dataset.


The best model (stopped after 20 epochs) achieves the following results on the evaluation set:


* Loss:0.7549
* Accuracy: 0.6806
* F1: 0.6783
* Precision: 0.6775
* Recall: 0.6806


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 #deberta-v2 #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