---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: finetuning_test
  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. -->

# finetuning_test

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: 0.6970
- Accuracy: 0.5
- F1-score: 0.6667
- Precision: 0.5
- Recall: 1.0

## 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: 1e-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: 2
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
| 0.7485        | 0.1   | 1    | 0.6990          | 0.5      | 0.6667   | 0.5       | 1.0    |
| 0.6785        | 0.2   | 2    | 0.6984          | 0.5      | 0.6667   | 0.5       | 1.0    |
| 0.6803        | 0.3   | 3    | 0.6982          | 0.5      | 0.6667   | 0.5       | 1.0    |
| 0.6517        | 0.4   | 4    | 0.6983          | 0.5      | 0.6667   | 0.5       | 1.0    |
| 0.7254        | 0.5   | 5    | 0.6980          | 0.5      | 0.6667   | 0.5       | 1.0    |
| 0.6979        | 0.6   | 6    | 0.6978          | 0.5      | 0.6667   | 0.5       | 1.0    |
| 0.7064        | 0.7   | 7    | 0.6975          | 0.5      | 0.6667   | 0.5       | 1.0    |
| 0.6709        | 0.8   | 8    | 0.6973          | 0.5      | 0.6667   | 0.5       | 1.0    |
| 0.7092        | 0.9   | 9    | 0.6971          | 0.5      | 0.6667   | 0.5       | 1.0    |
| 0.6975        | 1.0   | 10   | 0.6970          | 0.5      | 0.6667   | 0.5       | 1.0    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1