---
license: mit
base_model: microsoft/deberta-v3-small
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-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0636
- Precision: 0.6312
- Recall: 0.7311
- F1: 0.6775
- Accuracy: 0.9769

## 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   | 0.0843          | 0.4846    | 0.5294 | 0.5060 | 0.9683   |
| No log        | 2.0   | 110  | 0.0697          | 0.5695    | 0.7115 | 0.6326 | 0.9729   |
| No log        | 3.0   | 165  | 0.0652          | 0.6099    | 0.7423 | 0.6696 | 0.9754   |
| No log        | 4.0   | 220  | 0.0636          | 0.6445    | 0.7185 | 0.6795 | 0.9772   |
| No log        | 5.0   | 275  | 0.0636          | 0.6312    | 0.7311 | 0.6775 | 0.9769   |


### Framework versions

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