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---
license: mit
base_model: BAAI/bge-small-en-v1.5
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bge-small-en-v1.5-sms-spam
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. -->
# bge-small-en-v1.5-sms-spam
This model is a fine-tuned version of [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0328
- Accuracy: 0.9928
- Precision: 0.9928
- Recall: 0.9928
- F1: 0.9928
## 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: 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 | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 1.0 | 244 | 0.0481 | 0.9904 | 0.9904 | 0.9904 | 0.9904 |
| No log | 2.0 | 488 | 0.0435 | 0.9916 | 0.9918 | 0.9916 | 0.9917 |
| 0.0902 | 3.0 | 732 | 0.0379 | 0.9904 | 0.9904 | 0.9904 | 0.9903 |
| 0.0902 | 4.0 | 976 | 0.0350 | 0.9916 | 0.9916 | 0.9916 | 0.9916 |
| 0.0173 | 5.0 | 1220 | 0.0328 | 0.9928 | 0.9928 | 0.9928 | 0.9928 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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