---
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: 0.1882
- Precision: 0.6628
- Recall: 0.6836
- F1: 0.6730
- Accuracy: 0.9512

## 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  | 0.2799          | 0.4758    | 0.4403 | 0.4574 | 0.9202   |
| 0.3348        | 2.0   | 564  | 0.2225          | 0.5810    | 0.5940 | 0.5875 | 0.9396   |
| 0.3348        | 3.0   | 846  | 0.2105          | 0.6015    | 0.6149 | 0.6081 | 0.9389   |
| 0.1571        | 4.0   | 1128 | 0.1979          | 0.6732    | 0.6642 | 0.6687 | 0.9534   |
| 0.1571        | 5.0   | 1410 | 0.1882          | 0.6628    | 0.6836 | 0.6730 | 0.9512   |
| 0.0948        | 6.0   | 1692 | 0.2099          | 0.6196    | 0.6612 | 0.6397 | 0.9495   |
| 0.0948        | 7.0   | 1974 | 0.2251          | 0.6900    | 0.6776 | 0.6837 | 0.9540   |


### Framework versions

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