---
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: 0.2254
- Precision: 0.6447
- Recall: 0.6716
- F1: 0.6579
- Accuracy: 0.9475

## 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  | 0.2896          | 0.4849    | 0.4567 | 0.4704 | 0.9207   |
| 0.3471        | 2.0   | 564  | 0.2266          | 0.5677    | 0.5821 | 0.5748 | 0.9348   |
| 0.3471        | 3.0   | 846  | 0.2240          | 0.5925    | 0.6164 | 0.6042 | 0.9377   |
| 0.1655        | 4.0   | 1128 | 0.2015          | 0.6455    | 0.6522 | 0.6488 | 0.9478   |
| 0.1655        | 5.0   | 1410 | 0.2017          | 0.6431    | 0.6776 | 0.6599 | 0.9485   |
| 0.1072        | 6.0   | 1692 | 0.2095          | 0.6164    | 0.6522 | 0.6338 | 0.9455   |
| 0.1072        | 7.0   | 1974 | 0.2086          | 0.6556    | 0.6791 | 0.6672 | 0.9495   |
| 0.0758        | 8.0   | 2256 | 0.2278          | 0.6322    | 0.6672 | 0.6492 | 0.9466   |
| 0.0529        | 9.0   | 2538 | 0.2226          | 0.6429    | 0.6716 | 0.6569 | 0.9480   |
| 0.0529        | 10.0  | 2820 | 0.2254          | 0.6447    | 0.6716 | 0.6579 | 0.9475   |


### Framework versions

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