---
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
should probably proofread and complete it, then remove this comment. -->

# 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: 0.2053
- Precision: 0.6638
- Recall: 0.6836
- F1: 0.6735
- Accuracy: 0.9498

## 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  | 0.2811          | 0.4809    | 0.4896 | 0.4852 | 0.9235   |
| 0.3394        | 2.0   | 564  | 0.2218          | 0.5679    | 0.5866 | 0.5771 | 0.9377   |
| 0.3394        | 3.0   | 846  | 0.2205          | 0.5708    | 0.5776 | 0.5742 | 0.9347   |
| 0.1635        | 4.0   | 1128 | 0.2027          | 0.6290    | 0.6478 | 0.6382 | 0.9469   |
| 0.1635        | 5.0   | 1410 | 0.1895          | 0.6542    | 0.6806 | 0.6672 | 0.9504   |
| 0.106         | 6.0   | 1692 | 0.2055          | 0.6334    | 0.6448 | 0.6391 | 0.9470   |
| 0.106         | 7.0   | 1974 | 0.1992          | 0.6328    | 0.6687 | 0.6502 | 0.9502   |
| 0.0744        | 8.0   | 2256 | 0.2051          | 0.6804    | 0.6925 | 0.6864 | 0.9513   |
| 0.0522        | 9.0   | 2538 | 0.1998          | 0.6745    | 0.6866 | 0.6805 | 0.9502   |
| 0.0522        | 10.0  | 2820 | 0.2053          | 0.6638    | 0.6836 | 0.6735 | 0.9498   |


### Framework versions

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