---
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large_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. -->

# deberta-v3-large_test

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: 1.6938
- Accuracy: 0.788

## 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: 3e-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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 310  | 0.6067          | 0.784    |
| 0.5494        | 2.0   | 620  | 0.8963          | 0.786    |
| 0.5494        | 3.0   | 930  | 1.4195          | 0.814    |
| 0.1122        | 4.0   | 1240 | 1.5111          | 0.778    |
| 0.0298        | 5.0   | 1550 | 1.6544          | 0.77     |
| 0.0298        | 6.0   | 1860 | 1.6181          | 0.792    |
| 0.0086        | 7.0   | 2170 | 1.6938          | 0.788    |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2