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---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner-bert
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. -->
# ner-bert
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: 0.0002
- Precision: 1.0
- Recall: 0.9993
- F1: 0.9997
- Accuracy: 1.0000
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0005 | 0.1 | 250 | 0.0047 | 0.9998 | 0.9861 | 0.9929 | 0.9994 |
| 0.009 | 0.2 | 500 | 0.0041 | 0.9961 | 0.9864 | 0.9912 | 0.9994 |
| 0.0004 | 0.3 | 750 | 0.0024 | 0.9977 | 0.9895 | 0.9936 | 0.9995 |
| 0.0001 | 0.4 | 1000 | 0.0010 | 0.9984 | 0.9975 | 0.9980 | 0.9999 |
| 0.0001 | 0.51 | 1250 | 0.0008 | 1.0 | 0.9975 | 0.9987 | 0.9999 |
| 0.0001 | 0.61 | 1500 | 0.0005 | 1.0 | 0.9975 | 0.9987 | 0.9999 |
| 0.0003 | 0.71 | 1750 | 0.0003 | 1.0 | 0.9991 | 0.9995 | 1.0000 |
| 0.0001 | 0.81 | 2000 | 0.0002 | 1.0 | 0.9993 | 0.9997 | 1.0000 |
| 0.0 | 0.91 | 2250 | 0.0002 | 1.0 | 0.9993 | 0.9997 | 1.0000 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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