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---
license: mit
base_model: MoritzLaurer/deberta-v3-large-zeroshot-v2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine-tuned-MoritzLaurer-deberta-v3-large-zeroshot-v2.0-arceasy
  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. -->

# fine-tuned-MoritzLaurer-deberta-v3-large-zeroshot-v2.0-arceasy

This model is a fine-tuned version of [MoritzLaurer/deberta-v3-large-zeroshot-v2.0](https://huggingface.co/MoritzLaurer/deberta-v3-large-zeroshot-v2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8204
- Accuracy: 0.8175

## 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: 1.5e-05
- 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: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 141  | 0.4636          | 0.8333   |
| No log        | 2.0   | 282  | 0.5887          | 0.8175   |
| No log        | 3.0   | 423  | 0.5583          | 0.8316   |
| 0.3291        | 4.0   | 564  | 0.7024          | 0.8246   |
| 0.3291        | 5.0   | 705  | 0.7975          | 0.8246   |
| 0.3291        | 6.0   | 846  | 0.8204          | 0.8175   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1