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---
license: apache-2.0
base_model: sentence-transformers/paraphrase-multilingual-mpnet-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mpnet-multi-agri-classifier
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. -->
# mpnet-multi-agri-classifier
This model is a fine-tuned version of [sentence-transformers/paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3444
- Precision Macro: 0.8402
- Precision Weighted: 0.9196
- Recall Macro: 0.9042
- Recall Weighted: 0.9046
- F1-score: 0.8655
- Accuracy: 0.9046
## 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: 6.9e-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
- lr_scheduler_warmup_steps: 200
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted | F1-score | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:------------:|:---------------:|:--------:|:--------:|
| 0.393 | 1.0 | 334 | 0.2938 | 0.8528 | 0.9132 | 0.8773 | 0.9092 | 0.8641 | 0.9092 |
| 0.3213 | 2.0 | 668 | 0.3049 | 0.8299 | 0.9110 | 0.8885 | 0.8966 | 0.8534 | 0.8966 |
| 0.2591 | 3.0 | 1002 | 0.2561 | 0.8654 | 0.9226 | 0.8937 | 0.9184 | 0.8784 | 0.9184 |
| 0.1853 | 4.0 | 1336 | 0.3254 | 0.8386 | 0.9190 | 0.9034 | 0.9034 | 0.8641 | 0.9034 |
| 0.1119 | 5.0 | 1670 | 0.3444 | 0.8402 | 0.9196 | 0.9042 | 0.9046 | 0.8655 | 0.9046 |
### Framework versions
- Transformers 4.35.2
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.15.0
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