---
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-finetuned-ner-microsoft-disaster-cleaned
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/akku/huggingface/runs/bxmx75hr)
# deberta-finetuned-ner-microsoft-disaster-cleaned

This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0791
- Precision: 0.9251
- Recall: 0.9335
- F1: 0.9292
- Accuracy: 0.9808

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0908        | 1.0   | 1799 | 0.0765          | 0.9134    | 0.9236 | 0.9185 | 0.9798   |
| 0.0668        | 2.0   | 3598 | 0.0735          | 0.9284    | 0.9305 | 0.9295 | 0.9813   |
| 0.0515        | 3.0   | 5397 | 0.0756          | 0.9231    | 0.9315 | 0.9273 | 0.9804   |
| 0.0394        | 4.0   | 7196 | 0.0791          | 0.9251    | 0.9335 | 0.9292 | 0.9808   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1