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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: IKT_classifier_netzero_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_netzero_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: 0.9526
- Precision Macro: 0.7813
- Precision Weighted: 0.8164
- Recall Macro: 0.7734
- Recall Weighted: 0.7812
- F1-score: 0.7644
- Accuracy: 0.7812
## 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: 9.588722322096848e-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: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted | F1-score | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:------------:|:---------------:|:--------:|:--------:|
| No log | 1.0 | 114 | 0.8267 | 0.8056 | 0.8151 | 0.6601 | 0.6875 | 0.6418 | 0.6875 |
| No log | 2.0 | 228 | 0.4916 | 0.8095 | 0.8371 | 0.8290 | 0.8125 | 0.8113 | 0.8125 |
| No log | 3.0 | 342 | 0.4784 | 0.8535 | 0.8920 | 0.8682 | 0.875 | 0.8569 | 0.875 |
| No log | 4.0 | 456 | 0.8909 | 0.7813 | 0.8164 | 0.7734 | 0.7812 | 0.7644 | 0.7812 |
| 0.6167 | 5.0 | 570 | 0.6673 | 0.8242 | 0.8650 | 0.8649 | 0.8125 | 0.8260 | 0.8125 |
| 0.6167 | 6.0 | 684 | 0.7110 | 0.8413 | 0.8795 | 0.8845 | 0.8438 | 0.8505 | 0.8438 |
| 0.6167 | 7.0 | 798 | 1.3731 | 0.7778 | 0.8281 | 0.7702 | 0.7188 | 0.7380 | 0.7188 |
| 0.6167 | 8.0 | 912 | 0.9526 | 0.7813 | 0.8164 | 0.7734 | 0.7812 | 0.7644 | 0.7812 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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