---
license: mit
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: microsoft/deberta-v3-base
model-index:
- name: trainer
  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. -->

# trainer

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: 0.5146
- Accuracy: {'accuracy': 0.8154339363407374}

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy                         |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------------------:|
| 0.3938        | 1.0   | 2772  | 0.5646          | {'accuracy': 0.7842912754751545} |
| 0.3103        | 2.0   | 5544  | 0.5375          | {'accuracy': 0.7945958323792077} |
| 0.2796        | 3.0   | 8316  | 0.5112          | {'accuracy': 0.8124570643462331} |
| 0.2611        | 4.0   | 11088 | 0.5146          | {'accuracy': 0.8154339363407374} |


### Framework versions

- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2