---
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: 0.0681
- Precision: 0.6874
- Recall: 0.7731
- F1: 0.7278
- Accuracy: 0.9771

## 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   | 0.0748          | 0.5784    | 0.6457 | 0.6102 | 0.9699   |
| No log        | 2.0   | 110  | 0.0709          | 0.6174    | 0.7773 | 0.6882 | 0.9750   |
| No log        | 3.0   | 165  | 0.0670          | 0.6460    | 0.7899 | 0.7108 | 0.9758   |
| No log        | 4.0   | 220  | 0.0628          | 0.6966    | 0.7717 | 0.7322 | 0.9775   |
| No log        | 5.0   | 275  | 0.0681          | 0.6874    | 0.7731 | 0.7278 | 0.9771   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3