---
library_name: transformers
license: afl-3.0
base_model: Davlan/distilbert-base-multilingual-cased-ner-hrl
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: exp1
  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. -->

# exp1

This model is a fine-tuned version of [Davlan/distilbert-base-multilingual-cased-ner-hrl](https://huggingface.co/Davlan/distilbert-base-multilingual-cased-ner-hrl) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0695
- Precision: 0.9266
- Recall: 0.9478
- F1: 0.9371
- Accuracy: 0.9838

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0981        | 1.0   | 11771 | 0.0893          | 0.8784    | 0.9084 | 0.8932 | 0.9656   |
| 0.0752        | 2.0   | 23542 | 0.0737          | 0.8950    | 0.9317 | 0.9129 | 0.9740   |
| 0.0587        | 3.0   | 35313 | 0.0671          | 0.9067    | 0.9383 | 0.9222 | 0.9780   |
| 0.0444        | 4.0   | 47084 | 0.0684          | 0.9099    | 0.9462 | 0.9277 | 0.9802   |
| 0.0336        | 5.0   | 58855 | 0.0675          | 0.9257    | 0.9428 | 0.9342 | 0.9828   |
| 0.023         | 6.0   | 70626 | 0.0683          | 0.9218    | 0.9471 | 0.9343 | 0.9833   |
| 0.0216        | 7.0   | 82397 | 0.0695          | 0.9266    | 0.9478 | 0.9371 | 0.9838   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1