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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: 1.0515
- Precision Micro: 0.2570
- Precision Weighted: 0.2809
- Precision Samples: 0.2896
- Recall Micro: 0.6815
- Recall Weighted: 0.6815
- Recall Samples: 0.7119
- F1-score: 0.3907
- Accuracy: 0.0095
## 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 | 313 | 1.2909 | 0.1858 | 0.2078 | 0.1957 | 0.7185 | 0.7185 | 0.7222 | 0.2977 | 0.0 |
| 1.262 | 2.0 | 626 | 1.0875 | 0.2099 | 0.2605 | 0.2295 | 0.7852 | 0.7852 | 0.8071 | 0.3431 | 0.0 |
| 1.262 | 3.0 | 939 | 1.0171 | 0.2284 | 0.2612 | 0.2539 | 0.7630 | 0.7630 | 0.7746 | 0.3643 | 0.0095 |
| 1.0059 | 4.0 | 1252 | 1.0510 | 0.2519 | 0.2764 | 0.2914 | 0.7259 | 0.7259 | 0.7563 | 0.4013 | 0.0095 |
| 0.8421 | 5.0 | 1565 | 1.0515 | 0.2570 | 0.2809 | 0.2896 | 0.6815 | 0.6815 | 0.7119 | 0.3907 | 0.0095 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|