---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-v3-large-271-ver1
  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-large-271-ver1

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1014
- Precision: 0.9702
- Recall: 0.9702
- F1: 0.9702
- Accuracy: 0.9702

## 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: 12
- eval_batch_size: 12
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2626        | 1.0   | 896  | 0.1186          | 0.9561    | 0.9561 | 0.9561 | 0.9561   |
| 0.0699        | 2.0   | 1792 | 0.1014          | 0.9702    | 0.9702 | 0.9702 | 0.9702   |
| 0.0352        | 3.0   | 2688 | 0.1217          | 0.9680    | 0.9680 | 0.9680 | 0.9680   |
| 0.0115        | 4.0   | 3584 | 0.1857          | 0.9672    | 0.9672 | 0.9672 | 0.9672   |
| 0.0083        | 5.0   | 4480 | 0.2098          | 0.9680    | 0.9680 | 0.9680 | 0.9680   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1