---
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-multilingual-cased-finetuned-ner-geocorpus
  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. -->

# distilbert-base-multilingual-cased-finetuned-ner-geocorpus

This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1028
- Precision: 0.8079
- Recall: 0.8868
- F1: 0.8455
- Accuracy: 0.9747

## 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 276  | 0.1866          | 0.7323    | 0.6760 | 0.7030 | 0.9551   |
| 0.2877        | 2.0   | 552  | 0.1247          | 0.7870    | 0.7788 | 0.7829 | 0.9685   |
| 0.2877        | 3.0   | 828  | 0.1125          | 0.8547    | 0.7819 | 0.8167 | 0.9719   |
| 0.0858        | 4.0   | 1104 | 0.1043          | 0.8274    | 0.8463 | 0.8368 | 0.9739   |
| 0.0858        | 5.0   | 1380 | 0.1062          | 0.8349    | 0.8349 | 0.8349 | 0.9730   |
| 0.0424        | 6.0   | 1656 | 0.1028          | 0.8079    | 0.8868 | 0.8455 | 0.9747   |
| 0.0424        | 7.0   | 1932 | 0.1139          | 0.8586    | 0.8702 | 0.8644 | 0.9769   |
| 0.0225        | 8.0   | 2208 | 0.1229          | 0.8511    | 0.9024 | 0.8760 | 0.9765   |


### Framework versions

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