---
license: mit
tags:
- text-classification
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: deberta-v3-large-finetuned-synthetic-generated-only
  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-finetuned-synthetic-generated-only

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: 0.0094
- F1: 0.9839
- Precision: 0.9849
- Recall: 0.9828

## 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: 6e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:---------:|:------:|
| 0.009         | 1.0   | 10387 | 0.0104          | 0.9722 | 0.9919    | 0.9533 |
| 0.0013        | 2.0   | 20774 | 0.0067          | 0.9825 | 0.9844    | 0.9805 |
| 0.0006        | 3.0   | 31161 | 0.0077          | 0.9843 | 0.9902    | 0.9786 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1