--- license: mit tags: - generated_from_trainer base_model: Microsoft/Multilingual-MiniLM-L12-H384 metrics: - accuracy - f1 - precision - recall model-index: - name: my-model-MiniLM-Sentimento results: [] --- # my-model-MiniLM-Sentimento This model is a fine-tuned version of [Microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/Microsoft/Multilingual-MiniLM-L12-H384) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1247 - Accuracy: 0.9613 - F1: 0.85 - Precision: 1.0 - Recall: 0.7391 ## 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | 0.3826 | 1.0 | 91 | 0.3325 | 0.8839 | 0.3571 | 1.0 | 0.2174 | | 0.3332 | 2.0 | 182 | 0.2905 | 0.9032 | 0.5946 | 0.7857 | 0.4783 | | 0.284 | 3.0 | 273 | 0.2369 | 0.9355 | 0.7222 | 1.0 | 0.5652 | | 0.2313 | 4.0 | 364 | 0.2023 | 0.9355 | 0.7222 | 1.0 | 0.5652 | | 0.1983 | 5.0 | 455 | 0.1247 | 0.9613 | 0.85 | 1.0 | 0.7391 | ### Framework versions - Transformers 4.41.0 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1