---
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: 0.1929
- Precision: 0.7319
- Recall: 0.7531
- F1: 0.7423
- Accuracy: 0.9587

## 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  | 0.2132          | 0.5566    | 0.6224 | 0.5877 | 0.9403   |
| 0.28          | 2.0   | 564  | 0.1715          | 0.6793    | 0.7075 | 0.6931 | 0.9533   |
| 0.28          | 3.0   | 846  | 0.1507          | 0.7101    | 0.7469 | 0.7280 | 0.9586   |
| 0.0882        | 4.0   | 1128 | 0.1662          | 0.7368    | 0.7261 | 0.7315 | 0.9568   |
| 0.0882        | 5.0   | 1410 | 0.1718          | 0.7387    | 0.7448 | 0.7417 | 0.9579   |
| 0.0386        | 6.0   | 1692 | 0.1823          | 0.7078    | 0.7490 | 0.7278 | 0.9576   |
| 0.0386        | 7.0   | 1974 | 0.1969          | 0.7206    | 0.7490 | 0.7345 | 0.9574   |
| 0.0187        | 8.0   | 2256 | 0.1816          | 0.7349    | 0.7593 | 0.7469 | 0.9589   |
| 0.0101        | 9.0   | 2538 | 0.1928          | 0.7363    | 0.7531 | 0.7446 | 0.9584   |
| 0.0101        | 10.0  | 2820 | 0.1929          | 0.7319    | 0.7531 | 0.7423 | 0.9587   |


### Framework versions

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