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---
license: mit
base_model: microsoft/deberta-v3-xsmall
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-xsmall-beavertails-harmful-qa-classifier
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. -->
# deberta-v3-xsmall-beavertails-harmful-qa-classifier
This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3043
- Accuracy: 0.8716
- Macro F1: 0.8716
- Macro Precision: 0.8738
- Macro Recall: 0.8736
- Micro F1: 0.8716
- Micro Precision: 0.8716
- Micro Recall: 0.8716
## 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: 6e-06
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Macro Precision | Macro Recall | Micro F1 | Micro Precision | Micro Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|
| 0.3726 | 1.0 | 2349 | 0.3409 | 0.8573 | 0.8573 | 0.8581 | 0.8587 | 0.8573 | 0.8573 | 0.8573 |
| 0.3299 | 2.0 | 4698 | 0.3186 | 0.8669 | 0.8669 | 0.8697 | 0.8692 | 0.8669 | 0.8669 | 0.8669 |
| 0.3181 | 3.0 | 7047 | 0.3092 | 0.8683 | 0.8682 | 0.8715 | 0.8707 | 0.8683 | 0.8683 | 0.8683 |
| 0.3064 | 4.0 | 9396 | 0.3043 | 0.8716 | 0.8716 | 0.8738 | 0.8736 | 0.8716 | 0.8716 | 0.8716 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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