---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-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-uncased-finetuned-ner-harem

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2626
- Precision: 0.5556
- Recall: 0.5565
- F1: 0.5560
- Accuracy: 0.9336

## 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 282  | 0.3748          | 0.4065    | 0.2749 | 0.3280 | 0.9053   |
| 0.403         | 2.0   | 564  | 0.2924          | 0.5558    | 0.4705 | 0.5096 | 0.9266   |
| 0.403         | 3.0   | 846  | 0.2863          | 0.6589    | 0.5278 | 0.5861 | 0.9347   |
| 0.1961        | 4.0   | 1128 | 0.2626          | 0.5556    | 0.5565 | 0.5560 | 0.9336   |
| 0.1961        | 5.0   | 1410 | 0.2710          | 0.6279    | 0.5919 | 0.6094 | 0.9403   |
| 0.1074        | 6.0   | 1692 | 0.3046          | 0.6699    | 0.5818 | 0.6227 | 0.9408   |


### Framework versions

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