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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_conditional_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_conditional_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: 0.5371
- Precision Macro: 0.8714
- Precision Weighted: 0.8713
- Recall Macro: 0.8711
- Recall Weighted: 0.8712
- F1-score: 0.8712
- Accuracy: 0.8712
## 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: 4.112924307850544e-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: 400.0
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted | F1-score | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:------------:|:---------------:|:--------:|:--------:|
| 0.6658 | 1.0 | 698 | 0.7196 | 0.7391 | 0.7381 | 0.7102 | 0.7124 | 0.7028 | 0.7124 |
| 0.6301 | 2.0 | 1396 | 0.4965 | 0.8073 | 0.8075 | 0.8071 | 0.8069 | 0.8069 | 0.8069 |
| 0.5252 | 3.0 | 2094 | 0.5307 | 0.8300 | 0.8297 | 0.8279 | 0.8283 | 0.8279 | 0.8283 |
| 0.3513 | 4.0 | 2792 | 0.5261 | 0.8626 | 0.8627 | 0.8626 | 0.8627 | 0.8626 | 0.8627 |
| 0.2979 | 5.0 | 3490 | 0.5371 | 0.8714 | 0.8713 | 0.8711 | 0.8712 | 0.8712 | 0.8712 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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