---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: DeBERTa-finetuned-ner-S800
  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-finetuned-ner-S800

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0606
- Precision: 0.6730
- Recall: 0.7899
- F1: 0.7268
- Accuracy: 0.9783

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 55   | 0.0744          | 0.5840    | 0.6527 | 0.6164 | 0.9703   |
| No log        | 2.0   | 110  | 0.0639          | 0.6332    | 0.7689 | 0.6945 | 0.9764   |
| No log        | 3.0   | 165  | 0.0585          | 0.6424    | 0.7801 | 0.7046 | 0.9766   |
| No log        | 4.0   | 220  | 0.0581          | 0.6754    | 0.7955 | 0.7305 | 0.9785   |
| No log        | 5.0   | 275  | 0.0606          | 0.6730    | 0.7899 | 0.7268 | 0.9783   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3