---
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: deberta-v3-ft-news-sentiment-analisys
  results: []
---

<!-- 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. -->

# deberta-v3-ft-news-sentiment-analisys

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0233
- Precision: 0.9940
- Recall: 0.9940
- Accuracy: 0.9940
- F1: 0.9940

## 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: 2e-05
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
| No log        | 1.0   | 214  | 0.1865          | 0.9323    | 0.9323 | 0.9323   | 0.9323 |
| No log        | 2.0   | 428  | 0.0742          | 0.9771    | 0.9771 | 0.9771   | 0.9771 |
| 0.2737        | 3.0   | 642  | 0.0479          | 0.9855    | 0.9855 | 0.9855   | 0.9855 |
| 0.2737        | 4.0   | 856  | 0.0284          | 0.9923    | 0.9923 | 0.9923   | 0.9923 |
| 0.0586        | 5.0   | 1070 | 0.0233          | 0.9940    | 0.9940 | 0.9940   | 0.9940 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

## Citation

```BibText
@misc {manuel_romero_2024,
	author       = { {Manuel Romero} },
	title        = { deberta-v3-ft-financial-news-sentiment-analysis (Revision 7430ace) },
	year         = 2024,
	url          = { https://huggingface.co/mrm8488/deberta-v3-ft-financial-news-sentiment-analysis },
	doi          = { 10.57967/hf/1666 },
	publisher    = { Hugging Face }
}
```