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---
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 }
}
```
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