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

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: 0.0904
- Precision: 0.9322
- Recall: 0.9649
- F1: 0.9483
- Accuracy: 0.9813

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 58   | 0.1103          | 0.9316    | 0.9561 | 0.9437 | 0.9762   |
| No log        | 2.0   | 116  | 0.1157          | 0.9474    | 0.9474 | 0.9474 | 0.9796   |
| No log        | 3.0   | 174  | 0.1069          | 0.9153    | 0.9474 | 0.9310 | 0.9779   |
| No log        | 4.0   | 232  | 0.0904          | 0.9322    | 0.9649 | 0.9483 | 0.9813   |
| No log        | 5.0   | 290  | 0.0990          | 0.9322    | 0.9649 | 0.9483 | 0.9796   |
| No log        | 6.0   | 348  | 0.0964          | 0.9244    | 0.9649 | 0.9442 | 0.9813   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2