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

This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2169
- Precision: 0.6576
- Recall: 0.6851
- F1: 0.6711
- Accuracy: 0.9489

## 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  | 0.2950          | 0.4796    | 0.4388 | 0.4583 | 0.9183   |
| 0.3687        | 2.0   | 564  | 0.2216          | 0.5693    | 0.5821 | 0.5756 | 0.9362   |
| 0.3687        | 3.0   | 846  | 0.2170          | 0.5850    | 0.6060 | 0.5953 | 0.9373   |
| 0.1701        | 4.0   | 1128 | 0.1990          | 0.6352    | 0.6522 | 0.6436 | 0.9464   |
| 0.1701        | 5.0   | 1410 | 0.1978          | 0.6558    | 0.6910 | 0.6730 | 0.9481   |
| 0.1123        | 6.0   | 1692 | 0.1998          | 0.6378    | 0.6701 | 0.6536 | 0.9495   |
| 0.1123        | 7.0   | 1974 | 0.2112          | 0.6643    | 0.6851 | 0.6745 | 0.9490   |
| 0.0809        | 8.0   | 2256 | 0.2153          | 0.6571    | 0.6806 | 0.6686 | 0.9480   |
| 0.0572        | 9.0   | 2538 | 0.2133          | 0.6647    | 0.6836 | 0.6740 | 0.9502   |
| 0.0572        | 10.0  | 2820 | 0.2169          | 0.6576    | 0.6851 | 0.6711 | 0.9489   |


### Framework versions

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