---
license: cc-by-nc-sa-4.0
base_model: Babelscape/wikineural-multilingual-ner
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: wikineural-finetuned-ner
  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. -->

# wikineural-finetuned-ner

This model is a fine-tuned version of [Babelscape/wikineural-multilingual-ner](https://huggingface.co/Babelscape/wikineural-multilingual-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0198
- Precision: 0.9855
- Recall: 0.9833
- F1: 0.9844
- Accuracy: 0.9956

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 100  | 0.1020          | 0.8658    | 0.9134 | 0.8890 | 0.9693   |
| No log        | 2.0   | 200  | 0.0229          | 0.9828    | 0.9821 | 0.9824 | 0.9950   |
| No log        | 3.0   | 300  | 0.0198          | 0.9855    | 0.9833 | 0.9844 | 0.9956   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1