---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mpnet-adaptation_mitigation-classifier
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mpnet-adaptation_mitigation-classifier

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: 0.2117
- Precision Micro: 0.9175
- Precision Weighted: 0.9181
- Precision Samples: 0.9256
- Recall Micro: 0.9281
- Recall Weighted: 0.9281
- Recall Samples: 0.9314
- F1-score: 0.9263
- Accuracy: 0.9082

## 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: 8e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision Micro | Precision Weighted | Precision Samples | Recall Micro | Recall Weighted | Recall Samples | F1-score | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:---------------:|:--------------:|:--------:|:--------:|
| 0.3291        | 1.0   | 1051 | 0.2117          | 0.9175          | 0.9181             | 0.9256            | 0.9281       | 0.9281          | 0.9314         | 0.9263   | 0.9082   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3