---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: deberta-v3-base-finetuned-m_avoid_harm_seler
  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-base-finetuned-m_avoid_harm_seler

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5284
- Accuracy: 0.88
- F1: 0.9094

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6798        | 1.0   | 26   | 0.6119          | 0.945    | 0.9377 |
| 0.5411        | 2.0   | 52   | 0.4665          | 0.78     | 0.8484 |
| 0.4348        | 3.0   | 78   | 0.4732          | 0.71     | 0.8012 |
| 0.2908        | 4.0   | 104  | 0.3952          | 0.855    | 0.8943 |
| 0.2341        | 5.0   | 130  | 0.5284          | 0.88     | 0.9094 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1