---
library_name: transformers
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: base_bert_ner_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# base_bert_ner_model

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7122
- Precision: 0.2260
- Recall: 0.0256
- F1: 0.0460
- Accuracy: 0.8504

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 299  | 0.7522          | 0.1667    | 0.0008 | 0.0015 | 0.8492   |
| 0.7628        | 2.0   | 598  | 0.7353          | 0.2466    | 0.0140 | 0.0264 | 0.8499   |
| 0.7628        | 3.0   | 897  | 0.7247          | 0.2273    | 0.0233 | 0.0422 | 0.8509   |
| 0.7019        | 4.0   | 1196 | 0.7177          | 0.2619    | 0.0256 | 0.0466 | 0.8521   |
| 0.7019        | 5.0   | 1495 | 0.7122          | 0.2260    | 0.0256 | 0.0460 | 0.8504   |


### Framework versions

- Transformers 4.54.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2