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---
license: apache-2.0
base_model: sentence-transformers/all-mpnet-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: IKT_classifier_mitigation_best
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. -->
# IKT_classifier_mitigation_best
This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co./sentence-transformers/all-mpnet-base-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6517
- Precision Micro: 0.3667
- Precision Weighted: 0.4273
- Precision Samples: 0.4539
- Recall Micro: 0.7543
- Recall Weighted: 0.7543
- Recall Samples: 0.7982
- F1-score: 0.5422
- Accuracy: 0.1654
## 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: 3.6181464293180716e-05
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300.0
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision Micro | Precision Weighted | Precision Samples | Recall Micro | Recall Weighted | Recall Samples | F1-score | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:---------------:|:--------------:|:--------:|:--------:|
| No log | 1.0 | 398 | 1.0635 | 0.1718 | 0.2238 | 0.1763 | 0.7714 | 0.7714 | 0.7945 | 0.2794 | 0.0 |
| 1.2442 | 2.0 | 796 | 0.8827 | 0.2167 | 0.2522 | 0.2388 | 0.7543 | 0.7543 | 0.7863 | 0.3518 | 0.0 |
| 0.9539 | 3.0 | 1194 | 0.7579 | 0.2710 | 0.3279 | 0.2979 | 0.7543 | 0.7543 | 0.7932 | 0.4134 | 0.0150 |
| 0.8265 | 4.0 | 1592 | 0.6773 | 0.3377 | 0.3943 | 0.3937 | 0.7429 | 0.7429 | 0.7901 | 0.4961 | 0.0752 |
| 0.8265 | 5.0 | 1990 | 0.6517 | 0.3667 | 0.4273 | 0.4539 | 0.7543 | 0.7543 | 0.7982 | 0.5422 | 0.1654 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|