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---
license: apache-2.0
base_model: VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: my-model-Sabert-Sentimento
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. -->
# my-model-Sabert-Sentimento
This model is a fine-tuned version of [VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis](https://huggingface.co/VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3596
- Accuracy: 0.9161
- F1: 0.9167
- Precision: 0.9193
- Recall: 0.9161
## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2944 | 1.0 | 46 | 0.2173 | 0.9226 | 0.9204 | 0.9184 | 0.9226 |
| 0.1038 | 2.0 | 92 | 0.2623 | 0.9355 | 0.9331 | 0.9309 | 0.9355 |
| 0.0589 | 3.0 | 138 | 0.4238 | 0.9161 | 0.9196 | 0.9301 | 0.9161 |
| 0.0354 | 4.0 | 184 | 0.3488 | 0.9161 | 0.9167 | 0.9193 | 0.9161 |
| 0.0225 | 5.0 | 230 | 0.3596 | 0.9161 | 0.9167 | 0.9193 | 0.9161 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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