---
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: 0.1198
- Precision: 0.8118
- Recall: 0.8560
- F1: 0.8333
- Accuracy: 0.9732

## 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   | 276  | 0.2493          | 0.5422    | 0.4216 | 0.4744 | 0.9417   |
| 0.3195        | 2.0   | 552  | 0.1788          | 0.7273    | 0.7019 | 0.7143 | 0.9602   |
| 0.3195        | 3.0   | 828  | 0.1485          | 0.7550    | 0.7428 | 0.7488 | 0.9633   |
| 0.1376        | 4.0   | 1104 | 0.1542          | 0.7092    | 0.7956 | 0.7499 | 0.9619   |
| 0.1376        | 5.0   | 1380 | 0.1326          | 0.7449    | 0.8135 | 0.7777 | 0.9658   |
| 0.0887        | 6.0   | 1656 | 0.1152          | 0.8228    | 0.8305 | 0.8266 | 0.9728   |
| 0.0887        | 7.0   | 1932 | 0.1223          | 0.7721    | 0.8424 | 0.8057 | 0.9692   |
| 0.0639        | 8.0   | 2208 | 0.1184          | 0.7852    | 0.8501 | 0.8164 | 0.9721   |
| 0.0639        | 9.0   | 2484 | 0.1184          | 0.8252    | 0.8484 | 0.8366 | 0.9734   |
| 0.0505        | 10.0  | 2760 | 0.1198          | 0.8118    | 0.8560 | 0.8333 | 0.9732   |


### Framework versions

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