---
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-multilingual-cased-finetuned-ner-harem
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-multilingual-cased-finetuned-ner-harem

This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1777
- Precision: 0.7455
- Recall: 0.7780
- F1: 0.7614
- Accuracy: 0.9616

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 282  | 0.2251          | 0.5886    | 0.6203 | 0.6040 | 0.9414   |
| 0.2833        | 2.0   | 564  | 0.1686          | 0.6566    | 0.6784 | 0.6673 | 0.9505   |
| 0.2833        | 3.0   | 846  | 0.1603          | 0.6795    | 0.7303 | 0.7040 | 0.9565   |
| 0.0914        | 4.0   | 1128 | 0.1642          | 0.7310    | 0.7386 | 0.7348 | 0.9582   |
| 0.0914        | 5.0   | 1410 | 0.1545          | 0.7385    | 0.7676 | 0.7528 | 0.9595   |
| 0.0408        | 6.0   | 1692 | 0.1782          | 0.7179    | 0.7552 | 0.7361 | 0.9565   |
| 0.0408        | 7.0   | 1974 | 0.1840          | 0.7324    | 0.7552 | 0.7436 | 0.9599   |
| 0.0193        | 8.0   | 2256 | 0.1839          | 0.7324    | 0.7552 | 0.7436 | 0.9590   |
| 0.0107        | 9.0   | 2538 | 0.1788          | 0.7571    | 0.7697 | 0.7634 | 0.9624   |
| 0.0107        | 10.0  | 2820 | 0.1777          | 0.7455    | 0.7780 | 0.7614 | 0.9616   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1