---
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: 0.0559
- Precision: 0.95
- Recall: 0.9661
- F1: 0.9580
- Accuracy: 0.9856

## 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: 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   | 59   | 0.1342          | 0.8974    | 0.8898 | 0.8936 | 0.9633   |
| No log        | 2.0   | 118  | 0.0559          | 0.95      | 0.9661 | 0.9580 | 0.9856   |
| No log        | 3.0   | 177  | 0.0612          | 0.9417    | 0.9576 | 0.9496 | 0.9872   |
| No log        | 4.0   | 236  | 0.0605          | 0.9322    | 0.9322 | 0.9322 | 0.9840   |
| No log        | 5.0   | 295  | 0.0570          | 0.9496    | 0.9576 | 0.9536 | 0.9888   |
| No log        | 6.0   | 354  | 0.0579          | 0.9496    | 0.9576 | 0.9536 | 0.9888   |


### Framework versions

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