---
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large_test_9e-6
  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_9e-6

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: 1.1640
- Accuracy: 0.794

## 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: 9e-06
- 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  | 0.6535          | 0.772    |
| 0.6202        | 2.0   | 620  | 0.6425          | 0.798    |
| 0.6202        | 3.0   | 930  | 0.7958          | 0.782    |
| 0.1527        | 4.0   | 1240 | 1.0140          | 0.796    |
| 0.0448        | 5.0   | 1550 | 1.0381          | 0.796    |
| 0.0448        | 6.0   | 1860 | 1.1083          | 0.798    |
| 0.017         | 7.0   | 2170 | 1.1640          | 0.794    |


### Framework versions

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