---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: cyner_deberta
  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. -->

# cyner_deberta

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0685
- Precision: 0.7801
- Recall: 0.8110
- F1: 0.7952
- Accuracy: 0.9839

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1285        | 1.42  | 500  | 0.0762          | 0.7305    | 0.8033 | 0.7652 | 0.9823   |
| 0.041         | 2.84  | 1000 | 0.0685          | 0.7801    | 0.8110 | 0.7952 | 0.9839   |
| 0.024         | 4.26  | 1500 | 0.0796          | 0.7957    | 0.8008 | 0.7982 | 0.9855   |
| 0.0156        | 5.68  | 2000 | 0.0747          | 0.7836    | 0.8276 | 0.8050 | 0.9858   |
| 0.0106        | 7.1   | 2500 | 0.0817          | 0.7961    | 0.8327 | 0.8140 | 0.9859   |
| 0.0064        | 8.52  | 3000 | 0.0828          | 0.7942    | 0.8429 | 0.8178 | 0.9865   |
| 0.0049        | 9.94  | 3500 | 0.0858          | 0.7976    | 0.8352 | 0.8160 | 0.9865   |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1